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Saleem, Aban, and Jacob Blomgren. "Modelling Pupils’ Grades with Multiple Linear Regression Model." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-275672.
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This thesis was based on the subjects of mathematical statistics and industrial economics and management in order to analyze the grades of pupils in the final year of elementary school. The purpose was to find out what variables had a statistically significant impact on pupils’ final grades so that municipalities and schools could better understand what variables are important when trying to improve the average school results. A multiple regression model was used on data, obtained from the database of Skolverket, in order to examine what variables were statistically important. The final regression model acquired through a model reduction procedure showed that mostly structural covariates such as the academic background of pupils, percentage of female pupils and the percentage with Swedish background had a statistically significant impact on the academic performances of the students. R2 adjusted of the final model was 0.5289. The multiple regression model was discussed by referencing to previous research. In addition, the strategic management performance framework known as Balanced Scorecard which was introduced by Robert S. Kaplan and David P. Norton was used to discuss relevant key performance indicators to achieve the strategic objectives of schools.Detta examensarbete, inom ämnet för matematisk statistik och industriell ekonomi, genomfördes med syftet att analysera avgångsbetygen för år 9 i den svenska skolan. Syftet var att förstå vilka variabler som hade en statistisk signifikant påverkan på elevers avgångsbetyg, så kommuner kan förstå vilka variabler som är viktiga för att förbättra de genomsnittliga skolresultaten. En regressionsanalys utfördes, på data från Skolverket, för att se vilka variabler som var statistiskt signifikanta. Den slutgiltiga regressionsmodellen, erhållen genom iterativ reducering av variabler, visade att främst strukturella kovariat, som akademisk bakgrund hos elever, andel kvinnliga studenter och andel studenter med svensk bakgrund hade en signifikant betydelse på studenters akademiska resultat. Justerad R2 var 0.5289 för den slutgiltiga modellen. I diskussionen utvärderades modellen utifrån tidigare forskning. Vidare användes teorin om balanserat styrkort, utvecklat av Robert S. Kaplan och David P. Norton, för att diskutera relevanta nyckeltal för att uppnå strategiska mål för skolan.
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Gustafsson, Alexander, and Sebastian Wogenius. "Modelling Apartment Prices with the Multiple Linear Regression Model." Thesis, KTH, Matematisk statistik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-146735.
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This thesis examines factors that are of most statistical significance for the sales prices of apartments in the Stockholm City Centre. Factors examined are address, area, balcony, construction year, elevator, fireplace, floor number, maisonette, monthly fee, penthouse and number of rooms. On the basis of this examination, a model for predicting prices of apartments is constructed. In order to evaluate how the factors influence the price, this thesis analyses sales statistics and the mathematical method used is the multiple linear regression model. In a minor case-study and literature review, included in this thesis, the relationship between proximity to public transport and the prices of apartments in Stockholm are examined. The result of this thesis states that it is possible to construct a model, from the factors analysed, which can predict the prices of apartments in Stockholm City Centre with an explanation degree of 91% and a two million SEK confidence interval of 95%. Furthermore, a conclusion can be drawn that the model predicts lower priced apartments more accurately. In the case-study and literature review, the result indicates support for the hypothesis that proximity to public transport is positive for the price of an apartment. However, such a variable should be regarded with caution due to the purpose of the modelling, which differs between an individual application and a social economic applicationDenna uppsats undersöker faktorer som är av störst statistisk signifikans för priset vid försäljning av lägenheter i Stockholms innerstad. Faktorer som undersöks är adress, yta, balkong, byggår, hiss, kakelugn, våningsnummer, etage, månadsavgift, vindsvåning och antal rum. Utifrån denna undersökning konstrueras en modell för att predicera priset på lägenheter. För att avgöra vilka faktorer som påverkar priset på lägenheter analyseras försäljningsstatistik. Den matematiska metoden som används är multipel linjär regressionsanalys. I en mindre litteratur- och fallstudie, inkluderad i denna uppsats, undersöks sambandet mellan närhet till kollektivtrafik och priset på läagenheter i Stockholm. Resultatet av denna uppsats visar att det är möjligt att konstruera en modell, utifrån de faktorer som undersöks, som kan predicera priset på läagenheter i Stockholms innerstad med en förklaringsgrad på 91 % och ett två miljoner SEK konfidensintervall på 95 %. Vidare dras en slutsats att modellen preciderar lägenheter med ett lägre pris noggrannare. I litteratur- och fallstudien indikerar resultatet stöd för hypotesen att närhet till kollektivtrafik är positivt för priset på en lägenhet. Detta skall dock betraktas med försiktighet med anledning av syftet med modelleringen vilket skiljer sig mellan en individuell tillämpning och en samhällsekonomisk tillämpning.
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Alt, Raimund. "Multiple hypotheses testing in the linear regression model with applications to economics and finance /." Göttingen : Cuvillier, 2005. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=013081924&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.
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Kinns, David Jonathan. "Multiple case influence analysis with particular reference to the linear model." Thesis, University of Birmingham, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368427.
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Tao, Jinxin. "Comparison Between Confidence Intervals of Multiple Linear Regression Model with or without Constraints." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-theses/404.
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Regression analysis is one of the most applied statistical techniques. The sta- tistical inference of a linear regression model with a monotone constraint had been discussed in early analysis. A natural question arises when it comes to the difference between the cases of with and without the constraint. Although the comparison be- tween confidence intervals of linear regression models with and without restriction for one predictor variable had been considered, this discussion for multiple regres- sion is required. In this thesis, I discuss the comparison of the confidence intervals between a multiple linear regression model with and without constraints.
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Januario, Ana Paula Ferrari. "Análise estatística da produção de vitelão Mertolengo." Master's thesis, Universidade de Évora, 2021. http://hdl.handle.net/10174/29316.
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The work was intended to support the Association of mertolenga cattle breed in its breeding process and
decision making, namely in modeling the cost per day of production of the male mertolenga cattle, and
in identifying the variables that favor the sale of the animal as a product with a protected designation of
origin (PDO) seal. The database contained information on 716 male animals, of which 54 % went to the
slaughter that guarantees the PDO seal. We also had data on the cost structure production of the animals
from when it enters into the CTR to slaughter, in addition to the individual characteristics of each animal,
in particular, of its estimated breeding value.
To obtain the cost-per-day production model, multiple linear regression models and other generalized
linear models were used. For the classi cation of the animal as a PDO slaughter destination, a logistic
regression model was used.
When we comparing the generalized linear models tested, the multiple linear regression model was
con rmed as the best technique to explain the cost per day of production. For this model, it was found
that information such as weight at entry as well as di erent estimated breeding value positively in
uence
the cost of production.
With regard to logistic regression, weight at entry, age at entry and genetic values referring to
maternal capacity and calving interval are factors that enhance the animal being sold under the PDO seal; Sumário:
Com o trabalho desenvolvido nesta dissertação, pretendeu-se apoiar a Associação de produtores de bovinos
da raça mertolenga no seu processo de recria e nas tomadas de decisão, nomeadamente na modelação do
custo por dia de produção de bovinos machos da raça mertolenga, e na identificação das variáveis que
favorecem a venda do animal como um produto com selo de denominação de origem protegida (DOP).
A base de dados continha a informação de 716 animais machos, dos quais 54% foram para o abate que
garante o selo DOP, dados referentes _a estrutura de custo de produção dos animais desde a entrada no CTR
até o abate, além das características individuais de cada animal, em particular, dos seus valores genéticos.
Para obter o modelo do custo por dia de produção, utilizou-se modelos de regressão linear múltipla
e outros modelos lineares generalizados. Para a classificação do animal por destino de abate DOP, utilizou-se
um modelo de regressão logística. Quando se comparou os diferentes modelos lineares generalizados
testados, confirmou-se o modelo de regressão linear multipla como o mais adequado para explicar o custo
por dia de produção. Para este modelo, verificou-se que informações como o peso à entrada bem como
diferentes valores genéticos infuenciam de forma positiva o custo de produção.
No que diz respeito a regressão logística, o peso à entrada, a idade à entrada e os valores genéticos
referentes à capacidade maternal e intervalo entre partos são fatores potenciadores do animal ser vendido
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Yeasmin, Mahbuba 1965. "Multiple maxima of likelihood functions and their implications for inference in the general linear regression model." Monash University, Dept. of Econometrics and Business Statistics, 2003. http://arrow.monash.edu.au/hdl/1959.1/5821.
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Fridgeirsdottir, Gudrun A. "The development of a multiple linear regression model for aiding formulation development of solid dispersions." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/52176/.
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As poor solubility continues to be problem for new chemical entities (NCEs) in medicines development the use and interest in solid dispersions as a formulation-based solution has grown. Solid dispersions, where a drug is typically dispersed in a molecular state within an amorphous water-soluble polymer, present a good strategy to significantly enhance the effective drug solubility and hence bioavailability of drugs. The main drawback of this formulation strategy is the inherent instability of the amorphous form. With the right choice of polymer and manufacturing method, sufficient stability can be accomplished. However, finding the right combination of carrier and manufacturing method can be challenging, being labour, time and material costly. Therefore, a knowledge based support tool based upon a statistically significant data set to help with the formulation process would be of great value in the pharmaceutical industry. Here, 60 solid dispersion formulations were produced using ten, poorly soluble, chemically diverse APIs, three commonly used polymers and two manufacturing methods (spray drying and hot-melt extrusion). A long term stability study, up to one year, was performed on all formulations at accelerated conditions. Samples were regularly checked for the onset of crystallisation during the period, using mainly, polarised light microscopy. The stability data showed a large variance in stability between, methods, polymers and APIs. No obvious trends could be observed. Using statistical modelling, the experimental data in combination with calculated and predicted physicochemical properties of the APIs, several multiple linear regression (MLR) models were built. These had a good adjusted R2 and most showed good predictability in leave-one-out cross validations. Additionally, a validation on half of the models (eg. those based on spray-drying models) using an external dataset showed excellent predictability, with the correct ranking of formulations and accurate prediction of stability. In conclusion, this work has provided important insight into the complex correlations between the physical stability of amorphous solid dispersions and factors such as manufacturing method, carrier and properties of the API. Due to the expansive number of formulations studied here, which is far greater than previously published in the literature in a single study, more general conclusions can be drawn about these correlations than has previously been possible. This thesis has shown the potential of using well-founded statistical models in the formulation development of solid dispersion and given more insight into the complexity of these systems and how stability of these is dependent on multiple factors.
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Huschens, Stefan. "Einführung in die Ökonometrie." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-222629.
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Die Kapitel 1 bis 6 im ersten Teil dieses Skriptes beruhen auf einer Vorlesung Ökonometrie I, die zuletzt im WS 2001/02 gehalten wurde, die Kapitel 7 bis 16 beruhen auf einer Vorlesung Ökonometrie II, die zuletzt im SS 2006 gehalten wurde. Das achte Kapitel enthält eine komprimierte Zusammenfassung der Ergebnisse aus dem Teil Ökonometrie I.
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Löwe, Rakel, and Ida Schneider. "Automatic Differential Diagnosis Model of Patients with Parkinsonian Syndrome : A model using multiple linear regression and classification tree learning." Thesis, Uppsala universitet, Tillämpad kärnfysik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-413638.
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Parkinsonian syndrome is an umbrella term including several diseases with similar symptoms. PET images are key when differential diagnosing patients with parkinsonsian syndrome. In this work two automatic diagnosing models are developed and evaluated, with PET images as input, and a diagnosis as output. The two devoloped models are evaluated based on performance, in terms of sensitivity, specificity and misclassification error. The models consists of 1) regression model and 2) either a decision tree or a random forest. Two coefficients, alpha and beta, are introduced to train and test the models. The coefficients are the output from the regression model. They are calculated with multiple linear regression, with the patient images as dependent variables, and mean images of four patient groups as explanatory variables. The coefficients are the underlying relationship between the two. The four patient groups consisted of 18 healthy controls, 21 patients with Parkinson's disease, 17 patients with dementia with Lewi bodies and 15 patients with vascular parkinsonism. The models predict the patients with misclassification errors of 27% for the decision tree and 34% for the random forest. The patient group which is easiest to classify according to both models is healthy controls. The patient group which is hardest to classify is vascular parkinsonism. These results implies that alpha and beta are interesting outcomes from PET scans, and could, after further development of the model, be used as a guide when diagnosing in the models developed.
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Book, Emil, and Linus Ekelöf. "A Multiple Linear Regression Model To Assess The Effects of Macroeconomic Factors On Small and Medium-Sized Enterprises." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254298.
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Small and medium-sized enterprises (SMEs) have long been considered the backbone in any country’s economy for their contribution to growth and prosperity. It is therefore of great importance that the government and legislators adopt policies that optimise the success of SMEs. Recent concerns of an impending recession has made this topic even more relevant since small companies will have greater difficulty withstanding such an event. This thesis will focus on the effects of macroeconomic factors on SMEs in Sweden, with the usage of multiple linear regression. Data was collected for a 10 year period, from 2009 to 2019 at a monthly interval. The end result was a five variable model with an coefficient of determination of 98%.Små- och medelstora företag (SMEs) har länge varit ansedda som en av de viktigaste komponenterna i ett lands ekonomi, främst för deras bidrag till tillväxt och framgång. Det är därför mycket viktigt att regeringar och lagstiftare för en politik som främjar SMEs optimala tillväxt. Flera år av högkonjunktur och oro över kommande lågkonjunktur har gjort detta ämne ytterst relevant då små företag är de som kommer att drabbas värst av en svårare ekonomisk tillvaro. Denna rapport använder multipel linjär regression för att utvärdera effekterna av olika makroekonomiska faktorer på SMEs i Sverige. Data har insamlats månadsvis för en 10 årsperiod mellan 2009 till 2010. Resultatet blev en modell med fem variabler och en förklaringsgrad på 98%.
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Reis, Ricardo Jorge Antunes. "Avaliação de empreendimentos residenciais em Lisboa: estimativa de valor de um apartamento novo." Master's thesis, Instituto Superior de Economia e Gestão, 2008. http://hdl.handle.net/10400.5/523.
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Mestrado em Gestão e Avaliação ImobiliáriaA avaliação imobiliária em Portugal teve um grande desenvolvimento profissional nas últimas duas décadas, mas apresenta ainda muito potencial de melhoria técnicocientífica. O objectivo deste estudo é desenvolver e aplicar um modelo econométrico a uma amostra de oferta de apartamentos em empreendimentos residenciais novos em Lisboa, de gama média e média/alta, considerando as principais características que influenciam a formação do valor. O Modelo de Regressão Linear tem sido testado e aplicado em outros estudos empíricos, sendo considerado que responde às necessidades dos avaliadores imobiliários com um grau de fiabilidade aceitável. A amostra consiste em 539 apartamentos distribuídos por 102 empreendimentos. Recorre-se a um modelo seccional (cross-section) em que a variável dependente é o valor de oferta por m2, e variáveis independentes são a área bruta do apartamento,nº de lugares de estacionamento, prestígio da zona, distância ao pólo primário, etc.. O modelo utiliza variáveis semelhantes às que um avaliador “tradicional” implicitamente utiliza na sua prática. A vantagem de usar uma técnica estatística como a regressão múltipla é a de oferecer uma base científica ao trabalho empírico quando tradicionalmente os avaliadores recorriam mais a pressupostos subjectivos, baseados essencialmente na sua experiência e sensibilidade.
The professionalism in real estate valuation in Portugal improved substantially during the last two decades. However, it has still a large margin to develop in the utilization of new techniques with more scientific grounds. The objective of this study is to develop and apply an econometrical model to a sample to value apartments in new residential developments in Lisbon, of medium and medium/high standards, considering their value drivers. The Linear Regression Model has been applied and tested in other empirical research and is considered as a reliable technique for real estate valuation. The model was developed based on a sample of 539 apartments from 102 real estate developments. The cross-section model considered as the dependent variable the Bid Value per Square meter and the independent variables, the gross area, number of parking places, prestige of the zone, distance to the centre, etc.. The regression model uses variables that are implicitly used by “traditional” appraisers in their practice. However, the advantage of regression model is that brings a scientific base to the valuation instead of using subjective assumptions, based in the experience of the appraiser.
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Smith, Cheryl Ann. "A Multiple-Linear Regression Model to Predict Carotid Artery IMT in a Senior Population of Competitors at the Huntsman World Senior Games." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3002.
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Carotid intima-media thickness (cIMT) is a valid measure of cardiovascular disease (CVD). Physical activity appears to improve cIMT, however, research is inconclusive. This study investigated the relationship between physical activity (physical activity rating (PA-R)) and cardiovascular fitness (predicted VO2max , perceived functional ability (PFA)) and cIMT. Data collected from 341 seniors (≥50 years) competing in the Huntsman World Senior Games (HWSG) included blood lipids, inflammatory makers, blood glucose, blood pressure (BP) and anthropometric measurements of obesity and central adiposity. Multiple regression analysis was used to determine correlations of measured variables with cIMT. Two of the fitness related variables, PFA (r ≈ 0.1359; p = 0.012) and predicted VO2max (r ≈ 0.1475; p = 0.007) were significantly correlated to cIMT without controlling for confounding factors, but lost significance when adjustments for other CVD risk factors were included. PAR (r ≈ 0.0869; p = 0.111) was not significantly correlated to cIMT. Regression analysis indicated that the most predictive variables of cIMT we investigate were: age (t = 7.166, p = 0.000), gender (t = 3.310, p = 0.001), BMI (t = 1.892, p = 0.05), SBP (t = 3.952, p = 0.000), total cholesterol (TC) (t = 4.184, p = 0.000) and triglycerides (TRG) (t ≈ 3.466, p = 0.000), our R2 = .299, thus indicating these 6 variables account for about 30% of the variance in cIMT in seniors competing at HWSG. Physical activity and cardiovascular fitness influence other CVD risk factors and consequently may have an indirect impact on cIMT.
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Nguyen, Tien Hoang. "Development of transformation method of multispectral imagery into hyperspectral imagery for detailed identification of metal and geothermal resources-related minerals." Kyoto University, 2017. http://hdl.handle.net/2433/227611.
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Vieira, Luciano Henrique de Souza. "Dias trabalháveis para a colheita mecanizada da cana-de-açúcar no estado de São Paulo, com base em critérios agrometeorológicos." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/11/11152/tde-07032018-131134/.
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A determinação de dias trabalháveis para operações agrícolas de campo é de extrema importância para o dimensionamento de frotas de máquinas agrícolas. Isso é especialmente importante para a cultura da cana-de-açúcar, na qual as operações de campo se estendem por todo o ano, sendo a colheita a operação que mais danos pode trazer aos solos, quando executada sob condições inadequadas, já que essa ocorre por cerca de 8 a 10 meses. Com base nisso, o presente estudo teve como objetivos: definir os critérios para a determinação do número de dias trabalháveis (NDT) para colheita mecanizada da cana-de-açúcar no estado de São Paulo; determinar o NDT de diferentes regiões do estado de São Paulo com base em um critério geral e em critérios específicos para cada região; determinar a probabilidade de ocorrência de sequência do NDT por meio da cadeia de Markov; e elaborar uma planilha modelo para dimensionamento de frota para colheita mecanizada da cana-de-açúcar com base no NDT gerado pelo critério individual e geral. Para a definição dos critérios do NDT foram empregados dados de interrupção da moagem de 30 usinas no estado de São Paulo, para períodos variando de duas a cinco safras. Foram testados critérios de precipitação mínima (PREC), capacidade de água disponível (CAD) e limite da relação entre o armazenamento de água no solo e CAD (ARM/CAD) para se interromper a operação de colheita. De posse dos critérios de PREC, CAD e ARM/CAD para cada região e um critério geral, foram elaborados mapas do NDT para o estado de São Paulo, Posteriormente, definiu-se com base na cadeia de Markov, as probabilidades condicionais e, por meio dessas, as probabilidades de sequência de dias trabalháveis para cada decêndio do ano. Finalmente, foi elaborada uma planilha Excel® para o dimensionamento de frota de colhedoras de cana, com base no NDT. Os resultados mostraram que houve variação no critério para definição do NDT nas diferentes regiões do estado. No entanto, o uso de um critério geral para todo o estado, considerando-se a PREC de 3 mm, CAD de 40 mm e ARM/CAD de 90%, proporcionou resultados muito similares. O mapa de NDT gerado a partir do critério individual para cada região resultou em um erro médio de 24,9 dias por ano, ao passo que o mapa gerado a partir do critério geral resultou em um erro médio de 4,4 dias por ano, sendo este último mais adequado para a determinação do NDT médio para a colheita mecanizada de cana-de-açúcar. Com relação à probabilidade de sequência de dias trabalháveis, observou-se que nas regiões a oeste, noroeste e norte do estado há, em média, maiores probabilidades de ocorrência de dias trabalháveis, sendo que as maiores probabilidades ocorreram entre abril e setembro, com o primeiro decêndio de julho sendo o que tem os maiores valores. A probabilidade de o dia ser trabalhável dado que o anterior foi trabalhável manteve-se sempre com o mínimo em torno de 50% de probabilidade e com o máximo próximo de 90% em todas as regiões avaliadas. Finalmente, observou-se que a variação do NDT em função do critério usado (individual ou geral) não teve impacto expressivo nos custos de produção e totais. Com base nos resultados apresentados, conclui-se que a determinação correta do NDT é fundamental para o dimensionamento de sistemas de colheita da cana-de-açúcar.The determination of workable days for agricultural field operations is of extreme importance for dimensioning agricultural machinery fleets. This is especially important for sugarcane cultivation, in which field operations extend throughout the year, from 8 to 10 months per year. Based on this, the present study had as objectives: to define the criteria for determining the number of workable days (NWD) for sugarcane harvest in the state of São Paulo; to determine the NWD of different regions of the state of São Paulo based on general criteria and on specific criteria to each region; to determine the probability of a given NWD sequence by means of the Markov chain; and to elaborate a spreadsheet model for sizing the fleet to harvest sugarcane based on the NWD generated by the individual and general criteria For the definition of NWD criteria, the data from harvest interruption of 30 mills in the state of São Paulo, for periods ranging from two to five harvests, were used. The following criteria were tested: minimum precipitation (PREC); soil water holding capacity (SWHC) and the limit of the relationship between soil moisture storage and SWHC (ARM/SWHC), to define the harvest interruption. Based on these criteria for each region and also a general criteria, NWD maps were prepared for the state of São Paulo.. Afterwards, the conditional probabilities were defined on the basis of the Markov chain, and based on them the probabilities of sequences of working days were defined for all year long for each 10-day periods. Finally, an Excel® spreadsheet was programmed for dimensioning sugarcane harvest machines, based on the NWD. The results showed that there was variation in the criteria for the definition of NWD in the different regions of the state. However, the use of a general criteria for the whole state, considering PREC of 3 mm, SWHC of 40 mm and ARM/SWHC of 90% provided very similar results. The NWD maps generated from the individual criteria for each region generated an average error of 24.9 days per year whereas the map generated from the general criteria resulted in an average error of 4.4 days per year, being the last map the most suitable for determining the average NWD. Regarding the probability of sequences of workable days, it was observed that in the western, northwestern and northern regions of the state there is, on average, a greater probability of workable days, with the periods of greatest probability of workable days being between April and September. The probability of the a day be workable considering that the previous one was workable, always remained between 50% and 90% probability in all regions. Finally, for dimensioning havest mechines, it was observed that the variation of NWD as a function of the criteria used (individual or general) had no significant impact on production and total costs, but affected the total investment. It was concluded that the correct determination of NWD is fundamental for the design of sugarcane harvesting systems.
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Arruda, Filho Rubens Paes de. "Múltiplos e seus determinantes: um estudo para o mercado de ações brasileiro." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/13400.
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This study aims to investigate the relationship between three specifics multiples (Price/Earnings, Price/Book Value and Price/Sales) and its determinants (growth, payout ratio, risk, ROE and Margin), according to the theory presented by Aswath Damodaran. To verify these relationships, two different econometric methodologies were used: The Multiple Linear Regression and the Panel Data Model. The data collected are from the companies listed in the Stock Exchange Index of São Paulo - iBovespa. The results obtained by both methods were not the same as in theory, because some of the determinants did not show the expected behavior, and also were not statistically significant. The main contribution of this study is the use of Panel Data methodology to obtain the results.
Esse trabalho tem como objetivo investigar a relação entre três múltiplos específicos (Preço/Lucro, Preço/Valor Patrimonial e Preço/Vendas) e seus determinantes (crescimento, payout ratio, risco, ROE e margem líquida), de acordo com a teoria apresentada por Aswath Damodaran. Para verificar essas relações, foram utilizadas duas metodologias econométricas distintas: A Regressão Linear Múltipla e o Modelo de Dados em Painel. Os dados coletados são referentes às empresas listadas no índice de ações da Bolsa de Valores de São Paulo – iBOVESPA. Os resultados apurados por ambos os métodos não foram os mesmos verificados na teoria, pois alguns dos determinantes não apresentaram o comportamento esperado, e também não foram estatisticamente significantes. A principal contribuição desse trabalho é a utilização da metodologia de Dados em Painel para obter os resultados.
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CorrÃa, Denise Maria Morreira Chagas. "Indicadores de gestÃo do TCU e o desempenho dos Cursos no ENADE: um estudo de Cursos de GraduaÃÃo." Universidade Federal do CearÃ, 2013. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=10304.
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nÃo hÃAvaliar à uma forma de se obter feedback. O Tribunal de Contas da UniÃo (TCU) avalia as InstituiÃÃes Federais de Ensino Superior (IFES) por meio de nove indicadores de gestÃo, e o MinistÃrio da EducaÃÃo e Cultura (MEC), dentre outros indicadores, avalia os cursos das InstituiÃÃes de Ensino Superior (IES) por meio do Exame Nacional dos Estudantes (ENADE) dos cursos. Entre as abordagens sobre avaliaÃÃo educacional, tem-se o modelo CIPP, o qual avalia a instituiÃÃo de forma sistÃmica, com vistas à tomada de decisÃo, sob quatro Ãticas: contexto, insumos, processos e produtos. Esta pesquisa tem como objetivo geral investigar, sob a perspectiva do modelo CIPP de avaliaÃÃo, se os indicadores de gestÃo do TCU influenciam o desempenho dos cursos no ENADE. Portanto, quanto aos objetivos do trabalho, a pesquisa à explicativa. Quanto à abordagem do problema, à quantitativa, porque se utiliza de anÃlise de regressÃo linear mÃltipla para investigar a influÃncia das variÃveis independentes (indicadores de gestÃo do TCU) sobre a variÃvel dependente (ENADE dos cursos). Quanto Ãs tÃcnicas empregadas tem-se a documentaÃÃo indireta, aà incluÃda a pesquisa bibliogrÃfica e documental, bem como a pesquisa direta, aà incluÃda a pesquisa empÃrica, no Ãmbito das unidades acadÃmicas da Faculdade de EducaÃÃo (FACED), Faculdade de Direito (FADIR) e Faculdade de Economia, AdministraÃÃo, AtuÃria e Contabilidade (FEAAC) destinada ao teste das hipÃteses da pesquisa. Os resultados indicam que os cursos analisados possuem desempenhos diferentes, entretanto, a anÃlise de regressÃo mÃltipla aplicÃvel ao conjunto de observaÃÃes revelou que, entre os nove indicadores de gestÃo analisados, apenas o indicador funcionÃrio-equivalente por professor-equivalente (FEPE) nÃo influencia o resultado do ENADE e os demais indicadores do TCU que influenciam o resultado do ENADE se inserem nas quatro plataformas do modelo CIPP.
Evaluation is a way to obtain feedback. The Audit Court (Tribunal de Contas da UniÃo â TCU) evaluates Federal Institutions of Higher Education (IFES)â performances through nine management indicators and the Education and Culture Ministry (MEC) evaluates higher education institutions (IES)â courses, among others indicators, through the courses Students National Survey (ENADE). Among various approaches on educational assessment, the CIPP evaluation model evaluates the institution in a systematic way, with the purpose of decision making, about four points of view: context, inputs, processes and products. This research aims at investigating the CIPP evaluation model perspective, if the TCU indicators management influence the courses ENADE performance. By this work objectives, itâs an explanatory research. By the problem approach, itâs quantitative because it employs multiple linear regression analysis to investigate the independent variablesâ influence (indicators management TCU, per course) on the dependent variables (ENADE courses). As the techniques employed have to indirect documentation, including therein the literature and documents, as well as direct research, including therein the empirical research within the academic units FACED, FADIR and FEAAC, Federal University of Cearà (UFC) designed to test the research hypotheses. The results indicate that the courses object of analysis have different performances, however, the multiple regression analysis applied to the set of observations revealed that, among the nine TCU management indicators analyzed, only the gauge-equivalent employee per teacher-equivalent (FEPE) doesnât influence ENADE outcomes, and the other indicators which influence ENADE outcomes, has four platforms CIPP model include variables that explain the behavior of the dependent variable.
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Rodrigues, Stephanie Nancy da Veiga Jassy Barbosa. "Modelação e previsão da despesa em cuidados de saúde em Portugal." Master's thesis, Instituto Superior de Economia e Gestão, 2016. http://hdl.handle.net/10400.5/13147.
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Mestrado em Decisão Económica e EmpresarialEsta tese teve como objectivo a modelação e previsão em cuidados de saúde (privada, pública e total) recorrendo ao modelo ARIMA. Foi realizado um estudo econométrico sobre as variáveis potencialmente explicativas da evolução da despesa em cuidados de saúde em Portugal recorrendo ao modelo de Regressão Linear Múltipla. Para realizar a modelização e previsão das despesas em cuidados de saúde bem como para o estudo econométrico das despesas em cuidados de saúde, foi utilizado o software Eviews 9.0. O modelo ARIMA (2,1,2) de acordo com os critérios AIC e BIC mostrou ser o melhor modelo para previsões para as despesas em cuidados de saúde (privada, pública e total) em Portugal nos anos 2014 e 2015. O resultado das previsões para as despesas em cuidados de saúde (privada, pública e total) indica que se irá verificar um aumento. Este resultado indicou ser bastante positivo dado que a diferença entre o valor previsto e o valor real da despesa em cuidados de saúde em 2015 foi pequena. A mortalidade infantil, proxy da evolução tecnológica segundo Okunate & Murthy (2002) mostrou ser a variável com maior capacidade de explicação da variação na despesa em cuidados de saúde (privada, pública e total) em Portugal. Assim, a mortalidade parece ser uma boa proxy dos efeitos do progresso tecnológico embora Newhose (1992), Okunate & Murthy (2002) afirmarem que é necessário realizar investigações sobre a conceptualização, mensuração e a incorporação destes efeitos para a explicação da evolução da despesa em cuidados de saúde.
This theses had the purpose of modeling and forecast the healthcare expenses (private, public and total), using the ARIMA model. it was made an econometric study of the potentially explanatory variables of expenditure developments in health care in Portugal using the Multiple Linear Regression Model. To perform the modeling and forecasting of costs in health care and the econometric study of costs in health care, it was used the Eviews 9.0 software. The ARIMA (2,1,2) according to the AIC and BIC criteria was the best model to make forecasts for spending on private, public and total health care in Portugal in the years 2014 and 2015. The result of the forecasts for spending on private, public and total health care demonstrated that we will see an increase. This result indicated to be very positive as the difference between the predicted value and the real value of expenditure on health care in 2015 was small. Infant mortality, proxy of technological according with Okunate & Murthy (2002) proved to be the variable with the greatest capacity for the explanation on the variation of the spending on private health care, public and total health care in Portugal. Thus, mortality seems to be a good proxy of the effects of technological progress but Newhose (1992), Okunate & Murthy (2002) claim that it is necessary to carry out investigations regarding the conceptualization, measurement, and the incorporation of these effects to explain the evolution of expenditure in health care.
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Minas, Luís Guerra da Gama. "A evolução dos preços do imobiliário na União Europeia entre 2000-2017." Master's thesis, Instituto Superior de Economia e Gestão, 2019. http://hdl.handle.net/10400.5/20314.
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Mestrado em Ciências EmpresariaisOs preços do mercado imobiliário foram o tema escolhido para a elaboração deste Trabalho Final de Mestrado. A análise recaiu sobre os países pertencentes à União Europeia e o seu objeto de estudo é perceber qual foi a evolução dos preços do imobiliário e quais determinantes que mais influenciam o seu comportamento entre os anos de 2000 e 2017. Para compreender melhor o mercado imobiliário e conhecer os estudos já realizados foi elaborada uma revisão de literatura de forma a sustentar também a investigação desta dissertação. Escolhemos alguns determinantes sociais e económicos e correlacionámo-los com o índice de preços do imobiliário através de um modelo de Regressão Linear Múltiplo. Os principais resultados apontam determinantes como a crise financeira, a crise soberana ou as políticas do BCE como muito significativos, bem como a dívida pública a taxa de desemprego, entre outros. As conclusões do estudo vão no sentido de estudos anteriores e servem o propósito de fortalecer a informação sobre a complexidade do mercado imobiliário e os seus determinantes.
Real estate prices were the chosen theme for the preparation of this Master's Final Paper. The analysis is about the countries that belong to the European Union. The object of study is to understand the evolution of real estate prices and which determinants most influence their behaviour between 2000 and 2017. In order to better understand the real estate market and to know the already made studies, a literature review was elaborated to suport also the research of this dissertation. Social and economic determinants were chosen and correlated with the real estate prices índex, using a Multiple Liner Regression model. The main results point to determinants, such as the financial crisis or the ECB's policies as very significant, as well as the public dept and the unemplyment rate, among others. The study's findings are in the direction of previous studies and serve to a purpose of strengthening the information about the complexity of the real estate market and its determinants.
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Kracík, Adam. "Matematický model rozložení tvrdosti na opěrném válci." Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2011. http://www.nusl.cz/ntk/nusl-233957.
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The aim of this work is to get the best detailed knowledge about hardness distribution in first 60 mm below the surface of backing roll. To this end, a method for obtaining multi-dimensional polynomial regression was developed and then a computer program for its processing was written.Way of finding suitable regression surfaces and their subsequent interpretation, is a pivotal part of this work.
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Fearer, Todd Matthew. "Evaluating Population-Habitat Relationships of Forest Breeding Birds at Multiple Spatial and Temporal Scales Using Forest Inventory and Analysis Data." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/29243.
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Multiple studies have documented declines of forest breeding birds in the eastern United States, but the temporal and spatial scales of most studies limit inference regarding large scale bird-habitat trends. A potential solution to this challenge is integrating existing long-term datasets such as the U.S. Forest Service Forest Inventory and Analysis (FIA) program and U.S. Geological Survey Breeding Bird Survey (BBS) that span large geographic regions. The purposes of this study were to determine if FIA metrics can be related to BBS population indices at multiple spatial and temporal scales and to develop predictive models from these relationships that identify forest conditions favorable to forest songbirds. I accumulated annual route-level BBS data for 4 species guilds (canopy nesting, ground and shrub nesting, cavity nesting, early successional), each containing a minimum of five bird species, from 1966-2004. I developed 41 forest variables describing forest structure at the county level using FIA data from for the 2000 inventory cycle within 5 physiographic regions in 14 states (AL, GA, IL, IN, KY, MD, NC, NY, OH, PA, SC, TN, VA, and WV). I examine spatial relationships between the BBS and FIA data at 3 hierarchical scales: 1) individual BBS routes, 2) FIA units, and 3) and physiographic sections. At the BBS route scale, I buffered each BBS route with a 100m, 1km, and 10km buffer, intersected these buffers with the county boundaries, and developed a weighted average for each forest variable within each buffer, with the weight being a function of the percent of area each county had within a given buffer. I calculated 28 variables describing landscape structure from 1992 NLCD imagery using Fragstats within each buffer size. I developed predictive models relating spatial variations in bird occupancy and abundance to changes in forest and landscape structure using logistic regression and classification and regression trees (CART). Models were developed for each of the 3 buffer sizes, and I pooled the variables selected for the individual models and used them to develop multiscale models with the BBS route still serving as the sample unit. At the FIA unit and physiographic section scales I calculated average abundance/route for each bird species within each FIA unit and physiographic section and extrapolated the plot-level FIA variables to the FIA unit and physiographic section levels. Landscape variables were recalculated within each unit and section using NCLD imagery resampled to a 400 m pixel size. I used regression trees (FIA unit scale) and general linear models (GLM, physiographic section scale) to relate spatial variations in bird abundance to the forest and landscape variables. I examined temporal relationships between the BBS and FIA data between 1966 and 2000. I developed 13 forest variables from statistical summary reports for 4 FIA inventory cycles (1965, 1975, 1989, and 2000) within NY, PA, MD, and WV. I used linear interpolation to estimate annual values of each FIA variable between successive inventory cycles and GLMs to relate annual variations in bird abundance to the forest variables.
At the BBS route scale, the CART models accounted for > 50% of the variation in bird presence-absence and abundance. The logistic regression models had sensitivity and specificity rates > 0.50. By incorporating the variables selected for the models developed within each buffer (100m, 1km, and 10km) around the BBS routes into a multiscale model, I was able to further improve the performance of many of the models and gain additional insight regarding the contribution of multiscale influences on bird-habitat relationships. The majority of the best CART models tended to be the multiscale models, and many of the multiscale logistic models had greater sensitivity and specificity than their single-scale counter parts. The relatively fine resolution and extensive coverage of the BBS, FIA, and NLCD datasets coupled with the overlapping multiscale approach of these analyses allowed me to incorporate levels of variation in both habitat and bird occurrence and abundance into my models that likely represented a more comprehensive range of ecological variability in the bird-habitat relationships relative to studies conducted at smaller scales and/or using data at coarser resolutions.
At the FIA unit and physiographic section scales, the regression trees accounted for an average of 54.1% of the variability in bird abundance among FIA units, and the GLMs accounted for an average of 66.3% of the variability among physiographic sections. However, increasing the observational and analytical scale to the FIA unit and physiographic section decreased the measurement resolution of the bird abundance and landscape variables. This limits the applicability and interpretive strength of the models developed at these scales, but they may serve as indices to those habitat components exerting the greatest influences on bird abundance at these broader scales.
The GLMs relating average annual bird abundance to annual estimates of forest variables developed using statistical report data from the 1965, 1975, 1989, and 2000 FIA inventories explained an average of 62.0% of the variability in annual bird abundance estimates. However, these relationships were a function of both the general habitat characteristics and the trends in bird abundance specific to the 4-state region (MD, NY, PA, and WV) used for these analyses and may not be applicable to other states or regions. The small suite of variables available from the FIA statistical reports and multicollinearity among all forest variables further limited the applicability of these models. As with those developed at the FIA unit and physiographic sections scales, these models may serve as general indices to the habitat components exerting the greatest influences on bird abundance trends through time at regional scales.
These results demonstrate that forest variables developed from the FIA, in conjunction with landscape variables, can explain variations in occupancy and abundance estimated from BBS data for forest bird species with a variety of habitat requirements across spatial and temporal scales.Ph. D.
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Westby, Rebecca Marie. "Extreme temperature regimes during the cool season: recent observed behavior and low frequency mode modulation." Thesis, Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/42889.
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During the boreal cool season, regional climate in the United States is strongly impacted by extreme temperature regimes (ETRs), including both cold air outbreaks (CAOs) and warm waves (WWs), which have significant impacts on energy consumption, agriculture, as well as the human population. Using NCEP/NCAR and MERRA reanalysis data, the statistical characteristics of ETRs over three distinct geographical regions are studied: the Midwest (MW), Northeast Megalopolis (NE), and Deep South (SE). The regional long-term variability in the frequency and amplitude of ETRs is examined, and the modulation of these ETRs by low frequency modes is quantified.
ETR behavior is characterized using three different metrics applied to both T and Twc: 1) the number of extreme cold/warm days, 2) a seasonal cumulative "impact factor", and 3) a peak normalized anomaly value. A trend analysis reveals a significant downward trend in SE WW events from 1949-2011. Otherwise, no significant trends are found for ETRs in any of the other regions. Thus, these results indicate that there has not been any significant reduction in either the amplitude or frequency of CAOs over the United States during the period of analysis. In fact, for the SE region, the recent winters of 2009/2010 and 2010/2011 both rank among the top 5 in terms of CAO metrics. In addition, strong interannual variability in ETRs is evident from 1949-2011 in each region. Linear regression analysis is then used to determine the associations between ETR metrics and the seasonal mean state of several low frequency modes, and it is found that ETRs tend to be modulated by certain low frequency modes. For instance, in the SE region, there is a significant association between ETRs and the phase of the North Atlantic (or Arctic) Oscillation (NAO/AO), the Pacific North American (PNA) pattern (for WWs only), the Pacific Decadal Oscillation (PDO) and the El Niño-Southern Oscillation (for WWs only). Over the MW region, WWs are modulated by the NAO/AO and PNA patterns, while in the NE region, the AO, NAO (for WWs only) and PDO (for WWs only) are implicated. In addition, it is found that there is an asymmetry between the low frequency mode modulation of CAOs and WWs. Multiple linear regression analysis is then used to quantify the relative roles of the various low frequency modes in explaining interannual variability in ETR metrics, and reveals that various combinations of low frequency modes can explain anywhere between 10% and 50% of the variance in the ETR metrics.
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Lindström, Agnes, and Frida Persson. "Estimation of Hourly Origin Destination Trip Matrices for a Model of Norrköping." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-150135.
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During the last century, the number of car users has increased as an effect of the increasing population growth. To manage the environmental and infrastructural challenges that comes with a more congested traffic network, traffic planning has become of higher importance to analyze the current traffic state and to predict future capacity challenges and effects of investments. These analysis and evaluations are commonly performed in different traffic analysis tools, where updated and realistic traffic demand needs to be provided to ensure reasonable results. In this thesis, a macroscopic model of Norrköping municipality constructed in the traffic demand modelling software Visum and a daily Origin-Destination(OD)-matrix is considered. The goal of this thesis is to produce a method that modify the current daily demand matrix into hourly demand matrices, called hourly target matrices, that represents a typical weekday. The goal is also to implement and evaluate the OD-estimation algorithm Simultaneous Perturbation Stochastic Approximation (SPSA) to obtain updated and valid demand matrices for the network model of Norrköping. The method of dividing the daily demand matrix into hourly target matrices is based on the paper by Spiess %26 Suter (1990). The method makes use of the available daily trip purpose matrices combined with hourly link flow observations from 96 links in a multiple linear regression model to obtain 24 hourly demand matrices. The resulting matrices are compared with the link flow observations and has different levels of R^2-fit, the maximum fit is 85.79 % and the minimum fit is 55.89 %. The average R^2-value is 72 %. The OD-estimation based on SPSA is performed on the AM and PM peak hours. The algorithm is implemented in Python scripts that are called from Visum where the traffic assignments is calculated. The result is an increase in R^2-value since the link flow difference between estimated and observed link flow is decreased. In total, the estimated link flows are improved by 7.4 % in the AM peak hour and 15.6 % in the PM peak hour. The total absolute change in OD-demand is 3 871 trips for AM peak hour and 6 452 trips for the PM peak hour. The estimated OD-matrices are evaluated by qualitatively visualizing the difference in heat maps and in the quantitative measure structural similarity index. The result is no major structural change from the hourly target matrices which verifies that the information used when the target matrices is produced still is considered. The total demand increased in both hours, with 505 respectively 2 431 trips and flows in some OD-pairs has a very high percental change. This was restricted by adding a penalty term to the SPSA-algorithm on the PM peak hour. The result of penalized SPSA is a much less increase of total demand as well as less percental change of the OD-flows. Though, this to a cost of not decreasing the link flow difference in the same magnitude.
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Tamulis, Tomas. "Association between area socioeconomic status and hospital admissions for childhood and adult asthma." [Tampa, Fla.] : University of South Florida, 2005. http://purl.fcla.edu/fcla/etd/SFE0001134.
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Moreno, Betancur Margarita. "Regression modeling with missing outcomes : competing risks and longitudinal data." Thesis, Paris 11, 2013. http://www.theses.fr/2013PA11T076/document.
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Les données manquantes sont fréquentes dans les études médicales. Dans les modèles de régression, les réponses manquantes limitent notre capacité à faire des inférences sur les effets des covariables décrivant la distribution de la totalité des réponses prévues sur laquelle porte l'intérêt médical. Outre la perte de précision, toute inférence statistique requière qu'une hypothèse sur le mécanisme de manquement soit vérifiée. Rubin (1976, Biometrika, 63:581-592) a appelé le mécanisme de manquement MAR (pour les sigles en anglais de « manquant au hasard ») si la probabilité qu'une réponse soit manquante ne dépend pas des réponses manquantes conditionnellement aux données observées, et MNAR (pour les sigles en anglais de « manquant non au hasard ») autrement. Cette distinction a des implications importantes pour la modélisation, mais en général il n'est pas possible de déterminer si le mécanisme de manquement est MAR ou MNAR à partir des données disponibles. Par conséquent, il est indispensable d'effectuer des analyses de sensibilité pour évaluer la robustesse des inférences aux hypothèses de manquement.Pour les données multivariées incomplètes, c'est-à-dire, lorsque l'intérêt porte sur un vecteur de réponses dont certaines composantes peuvent être manquantes, plusieurs méthodes de modélisation sous l'hypothèse MAR et, dans une moindre mesure, sous l'hypothèse MNAR ont été proposées. En revanche, le développement de méthodes pour effectuer des analyses de sensibilité est un domaine actif de recherche. Le premier objectif de cette thèse était de développer une méthode d'analyse de sensibilité pour les données longitudinales continues avec des sorties d'étude, c'est-à-dire, pour les réponses continues, ordonnées dans le temps, qui sont complètement observées pour chaque individu jusqu'à la fin de l'étude ou jusqu'à ce qu'il sorte définitivement de l'étude. Dans l'approche proposée, on évalue les inférences obtenues à partir d'une famille de modèles MNAR dits « de mélange de profils », indexés par un paramètre qui quantifie le départ par rapport à l'hypothèse MAR. La méthode a été motivée par un essai clinique étudiant un traitement pour le trouble du maintien du sommeil, durant lequel 22% des individus sont sortis de l'étude avant la fin.Le second objectif était de développer des méthodes pour la modélisation de risques concurrents avec des causes d'évènement manquantes en s'appuyant sur la théorie existante pour les données multivariées incomplètes. Les risques concurrents apparaissent comme une extension du modèle standard de l'analyse de survie où l'on distingue le type d'évènement ou la cause l'ayant entrainé. Les méthodes pour modéliser le risque cause-spécifique et la fonction d'incidence cumulée supposent en général que la cause d'évènement est connue pour tous les individus, ce qui n'est pas toujours le cas. Certains auteurs ont proposé des méthodes de régression gérant les causes manquantes sous l'hypothèse MAR, notamment pour la modélisation semi-paramétrique du risque. Mais d'autres modèles n'ont pas été considérés, de même que la modélisation sous MNAR et les analyses de sensibilité. Nous proposons des estimateurs pondérés et une approche par imputation multiple pour la modélisation semi-paramétrique de l'incidence cumulée sous l'hypothèse MAR. En outre, nous étudions une approche par maximum de vraisemblance pour la modélisation paramétrique du risque et de l'incidence sous MAR. Enfin, nous considérons des modèles de mélange de profils dans le contexte des analyses de sensibilité. Un essai clinique étudiant un traitement pour le cancer du sein de stade II avec 23% des causes de décès manquantes sert à illustrer les méthodes proposéesMissing data are a common occurrence in medical studies. In regression modeling, missing outcomes limit our capability to draw inferences about the covariate effects of medical interest, which are those describing the distribution of the entire set of planned outcomes. In addition to losing precision, the validity of any method used to draw inferences from the observed data will require that some assumption about the mechanism leading to missing outcomes holds. Rubin (1976, Biometrika, 63:581-592) called the missingness mechanism MAR (for “missing at random”) if the probability of an outcome being missing does not depend on missing outcomes when conditioning on the observed data, and MNAR (for “missing not at random”) otherwise. This distinction has important implications regarding the modeling requirements to draw valid inferences from the available data, but generally it is not possible to assess from these data whether the missingness mechanism is MAR or MNAR. Hence, sensitivity analyses should be routinely performed to assess the robustness of inferences to assumptions about the missingness mechanism. In the field of incomplete multivariate data, in which the outcomes are gathered in a vector for which some components may be missing, MAR methods are widely available and increasingly used, and several MNAR modeling strategies have also been proposed. On the other hand, although some sensitivity analysis methodology has been developed, this is still an active area of research. The first aim of this dissertation was to develop a sensitivity analysis approach for continuous longitudinal data with drop-outs, that is, continuous outcomes that are ordered in time and completely observed for each individual up to a certain time-point, at which the individual drops-out so that all the subsequent outcomes are missing. The proposed approach consists in assessing the inferences obtained across a family of MNAR pattern-mixture models indexed by a so-called sensitivity parameter that quantifies the departure from MAR. The approach was prompted by a randomized clinical trial investigating the benefits of a treatment for sleep-maintenance insomnia, from which 22% of the individuals had dropped-out before the study end. The second aim was to build on the existing theory for incomplete multivariate data to develop methods for competing risks data with missing causes of failure. The competing risks model is an extension of the standard survival analysis model in which failures from different causes are distinguished. Strategies for modeling competing risks functionals, such as the cause-specific hazards (CSH) and the cumulative incidence function (CIF), generally assume that the cause of failure is known for all patients, but this is not always the case. Some methods for regression with missing causes under the MAR assumption have already been proposed, especially for semi-parametric modeling of the CSH. But other useful models have received little attention, and MNAR modeling and sensitivity analysis approaches have never been considered in this setting. We propose a general framework for semi-parametric regression modeling of the CIF under MAR using inverse probability weighting and multiple imputation ideas. Also under MAR, we propose a direct likelihood approach for parametric regression modeling of the CSH and the CIF. Furthermore, we consider MNAR pattern-mixture models in the context of sensitivity analyses. In the competing risks literature, a starting point for methodological developments for handling missing causes was a stage II breast cancer randomized clinical trial in which 23% of the deceased women had missing cause of death. We use these data to illustrate the practical value of the proposed approaches
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Rodrigues, João Manuel Pereira. "Especificação de um modelo hedónico de preços de habitação para Portugal." Master's thesis, Instituto Superior de Economia e Gestão, 2008. http://hdl.handle.net/10400.5/919.
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Mestrado em Gestão e Avaliação ImobiliáriaA teoria dos preços hedónicos tem aplicação prática no estudo de mercados implícitos, nos quais são transaccionados bens heterogéneos. Estes bens resultam da combinação de um conjunto de bens homogéneos, cujas características são bem identificadas pelos consumidores e produtores, mas para os quais não há um mercado específico, pelo que os consumidores não os podem adquirir isoladamente estando, por isso, limitados à aquisição conjunta de diferentes combinações de atributos, por um preço global. A habitação é um exemplo claro de um bem heterogéneo. No presente trabalho de dissertação, faz-se a aplicação da teoria dos preços hedónicos ao estudo dos preços no mercado da habitação, no território de Portugal continental. Para o efeito recorre-se exclusivamente a informação que, fruto da crescente utilização e divulgação da informática e em particular da Internet, se encontra actualmente disponível em portais especializados do imobiliário. Apresentam-se os resultados e as conclusões que decorrem desta abordagem.
The theory of the hedonic prices has practical application in the study of implicit markets, in which are traded heterogenous goods. These goods are the result from the combination of homogenous goods, whose attributes are well identified by the consumers and producers, but for which there is not a specific market, therefore the consumers cannot acquire them separately, being, by that, limited to the combined acquisition of bundles of characteristics, for a global price. Housing is a clear example of a heterogenous good. In the present work of dissertation, the theory of the hedonic prices is applied to the study of the prices in the housing market, in the territory of Portugal continental. For this purpose, as result of the growing utilization and disclosure of data processing and in specific of the Internet, information currently available in web sites specialized in real estate is used. The results and the conclusions that elapse from this approach are presented.
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Zahid, Saman. "Comparing Resource Abundance And Intake At The Reda And Wisla River Estuaries." Thesis, Linköpings universitet, Statistik och maskininlärning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-172770.
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The migratory birds stop at different stopover sites during migration. The presence of resources in these stopover sites is essential to regain the energy of these birds. This thesis aims to compare the resource abundance and intake at the two stopover sites: Reda and Wisla river estuaries. How a bird's mass changes during its stay at an estuary is considered as a proxy for the resource abundance of a site. The comparison is made on different subsets, including those which has incomplete data, i.e. next day is not exactly one day after the previous capture. Multiple linear regression, Generalized additive model and Linear mixed effect model are used for analysis. Expectation maximization and an iterative predictive process are implemented to deal with incomplete data. We found that Reda has higher resource abundance and intake as compared to that of Wisla river estuary.
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Forslund, Gustaf, and David Åkesson. "Predicting share price by using Multiple Linear Regression." Thesis, KTH, Farkost och flyg, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-140645.
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The aim of the project was to design a multiple linear regression model and use it to predict the share’s closing price for 44 companies listed on the OMX Stockholm stock exchange’s Large Cap list. The model is intended to be used as a day trading guideline i.e. today’s information is used to predict tomorrow’s closing price. The regression was done in Microsoft Excel 2010[18] by using its built-in function LINEST. The LINEST-function uses the dependent variable y and all the covariates x to calculate the β-value belonging to each covariate. Several multiple linear regression models were created and their functionality was tested, but only seven models were better than chance i.e. more than 50 % in the right direction. To determine the most suitable model out of the remaining seven, Akaike’s Information Criterion (AIC), was applied. The covariates used in the final model were; Dow Jones closing price, Shanghai opening price, conjuncture, oil price, share’s opening price, share’s highest price, share’s lowest price, lending rate, reports, positive/negative insider trading, payday, positive/negative price target, number of completed transactions during one day, OMX Stockholm closing price, TCW index, increasing closing price three days in a row and decreasing closing price three days in a row. The maximum average deviation between the predicted closing price and the real closing price of all the 44 shares predicted were 6,60 %. In predicting the correct direction (increase or decrease) of the 44 shares an average of 61,72 % were achieved during the time period 2012-02-22 to 2013-02-20. If investing 50.000 SEK in each company i.e. a total investment of 2.2 million SEK, the total yield when using the regression model during the year 2012-02-22 to 2013-02-20 would have been 259.639 SEK (11,80 %) compared to 184.171 SEK (8,37 %) if the shares were never to be traded with during the same period of time. Of the 44 companies analysed, 31 (70,45 %) of them were profitable when using the regression model during the year compared to 30 (68,18 %) if the shares were never to be sold during the same period of time. The difference in yield in percentage between the model and keeping the shares for the year was 40,98 %.
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Fabio, Lizandra Castilho. "Erros não detectáveis no processo de estimação de estado em sistemas elétricos de potência." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-01032016-120822/.
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Na tentativa de contornar os problemas ainda existentes para a detecção e identificação de erros grosseiros (EGs) no processo de estimação de estado em sistemas elétricos de potência (EESEP), realiza-se, neste trabalho, uma análise da formulação dos estimadores aplicados a sistemas elétricos de potência, em especial, o de mínimos quadrados ponderados, tendo em vista evidenciar as limitações dos mesmos para o tratamento de EGs. Em razão da dificuldade de detectar EGs em medidas pontos de alavancamento, foram também analisadas as metodologias desenvolvidas para identificação de medidas pontos de alavancamento. Através da formulação do processo de EESEP como um problema de álgebra linear, demonstra-se o porquê da impossibilidade de detectar EGs em determinadas medidas redundantes, sendo proposto, na seqüência, um método para identificação de medidas pontos de alavancamento. Para reduzir os efeitos maléficos dessas medidas no processo de EESEP verifica-se a possibilidade de aplicar outras técnicas estatísticas para o processamento de EGs, bem como técnicas para obtenção de uma matriz de ponderação adequada.To overcome the problems still existent for gross errors (GEs) detection and identification in the process of power system state estimation (PSSE), the formulations of the estimators applied to power systems are analyzed, specially, the formulation of the weighted squares estimator. These analyses were performed to show the limitations of these estimators for GEs processing. As leverage points (LP) represent a problem for GEs processing, methodologies for LP identification were also verified. By means of the linear formulation of the PSSE process, the reason for the impossibility of GEs detection in some redundant measurements is shown and a method for LP identification is proposed. To minimize the bad effects of the LP to the PSSE process, the possibility of applying other statistic techniques for GEs processing, as well as techniques to estimate an weighting matrix are also analyzed.
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Ollikainen, Kati. "PARAMETER ESTIMATION IN LINEAR REGRESSION." Doctoral diss., University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4138.
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Today increasing amounts of data are available for analysis purposes and often times for resource allocation. One method for analysis is linear regression which utilizes the least squares estimation technique to estimate a model's parameters. This research investigated, from a user's perspective, the ability of linear regression to estimate the parameters' confidence intervals at the usual 95% level for medium sized data sets. A controlled environment using simulation with known data characteristics (clean data, bias and or multicollinearity present) was used to show underlying problems exist with confidence intervals not including the true parameter (even though the variable was selected). The Elder/Pregibon rule was used for variable selection. A comparison of the bootstrap Percentile and BCa confidence interval was made as well as an investigation of adjustments to the usual 95% confidence intervals based on the Bonferroni and Scheffe multiple comparison principles. The results show that linear regression has problems in capturing the true parameters in the confidence intervals for the sample sizes considered, the bootstrap intervals perform no better than linear regression, and the Scheffe method is too wide for any application considered. The Bonferroni adjustment is recommended for larger sample sizes and when the t-value for a selected variable is about 3.35 or higher. For smaller sample sizes all methods show problems with type II errors resulting from confidence intervals being too wide.Ph.D.
Department of Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering and Management Systems
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Esler, William Kevin. "On the development and application of indirect site indexes based on edaphoclimatic variables for commercial forestry in South Africa." Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/20145.
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Thesis (MScFor)--Stellenbosch University, 2012.ENGLISH ABSTRACT: Site Index is used extensively in modern commercial forestry both as an indicator of current and future site potential, but also as a means of site comparison. The concept is deeply embedded into current forest planning processes, and without it empirical growth and yield modelling would not function in its present form. Most commercial forestry companies in South Africa currently spend hundreds of thousands of Rand annually collecting growth stock data via inventory, but spend little or no money on the default compartment data (specifically Site Index) which is used to estimate over 90% of the product volumes in their long term plans. A need exists to construct reliable methods to determine Site Index for sites which have not been physically measured (the socalled "default", or indirect Site Index). Most previous attempts to model Site Index have used multiple linear regression as the model, alternative methods have been explored in this thesis: Regression tree analysis, random forest analysis, hybrid or model trees, multiple linear regression, and multiple linear regression using regression trees to identify the variables. Regression tree analysis proves to be ideally suited to this type of data, and a generic model with only three site variables was able to capture 49.44 % of the variation in Site Index. Further localisation of the model could prove to be commercially useful. One of the key assumptions associated with Site Index, that it is unaffected by initial planting density, was tested using linear mixed effects modelling. The results show that there may well be role played by initial stocking in some species (notably E. dunnii and E. nitens), and that further work may be warranted. It was also shown that early measurement of dominant height results in poor estimates of Site Index, which will have a direct impact on inventory policies and on data to be included in Site Index modelling studies. This thesis is divided into six chapters: Chapter 1 contains a description of the concept of Site Index and it's origins, as well as, how the concept is used within the current forest planning processes. Chapter 2 contains an analysis on the influence of initial planted density on the estimate of Site Index. Chapter 3 explores the question of whether the age at which dominant height is measured has any effect on the quality of Site Index estimates. Chapter 4 looks at various modelling methodologies and compares the resultant models. Chapter 5 contains conclusions and recommendations for further study, and finally Chapter 6 discusses how any new Site Index model will effect the current planning protocol.
AFRIKAANSE OPSOMMING: Hedendaagse kommersiële bosbou gebruik groeiplek indeks (Site Index) as 'n aanduiding van huidige en toekomstige groeiplek moontlikhede, asook 'n metode om groeiplekke te vergelyk. Hierdie beginsel is diep gewortel in bestaande beplanningsprosesse en daarsonder kan empiriese groeien opbrengsmodelle nie in hul huidige vorm funksioneer nie. SuidAfrikaanse bosboumaatskappye bestee jaarliks groot bedrae geld aan die versameling van groeivoorraad data deur middel van opnames, maar weinig of geen geld word aangewend vir die insameling van ongemete vak data (veral groeiplek indeks) nie. Ongemete vak data word gebuik om meer as 90% van die produksie volume te beraam in langtermyn beplaning. 'n Behoefte bestaan om betroubare metodes te ontwikkel om groeiplek indeks te bereken vir groeiplekke wat nog nie opgemeet is nie. Die meeste vorige pogings om groeiplek indeks te beraam het meervoudige linêre regressie as model gebruik. Alternatiewe metodes is ondersoek; naamlik regressieboom analise, ewekansige woud analise, hibriedeof modelbome, meervoudige linêre regressie en meervoudige linêre regressie waarin die veranderlike faktore bepaal is deur regressiebome. Regressieboom analise blyk geskik te wees vir hierdie tipe data en 'n veralgemeende model met slegs drie groeiplek veranderlikes dek 49.44 % van die variasie in groeiplek indeks. Verdere lokalisering van die model kan dus van kommersiële waarde wees. 'n Sleutel aanname is gemaak dat aanvanklike plantdigtheid nie 'n invloed op groeiplek indeks het nie. Hierdie aanname is getoets deur linêre gemengde uitwerkings modelle. Die toetsuitslag dui op 'n moontlikheid dat plantdigtheid wel 'n invloed het op sommige spesies (vernaamlik E. dunnii en E. nitens) en verdere navorsing kan daarom geregverdig word. Dit is ook bewys dat metings van jonger bome vir dominante hoogtes gee aanleiding tot swak beramings van groeiplek indekse. Gevolglik sal hierdie toestsuitslag groeivoorraad opname beleid, asook die data wat vir groeiplek indeks modellering gebruik word, beïnvloed. Hierdie tesis word in ses hoofstukke onderverdeel. Hoofstuk een bevat 'n beskrywing van die beginsel van groeiplek indeks, die oorsprong daarvan, asook hoe die beginsel tans in huidige bosbou beplannings prosesse toegepas word. Hoofstuk twee bestaan uit ń ontleding van die invloed van aanvanklike plantdigtheid op die beraming van groeplek indeks. In hoofstuk drie word ondersoek wat die moontlike invloed is van die ouderdom waarop metings vir dominante hoogte geneem word, op die kwaliteit van groeplek indeks beramings het. Hoofstuk vier verken verskeie modelle metodologieë en vergelyk die uitslaggewende modelle. Hoofstuk vyf bevat gevolgtrekkings en voorstelle vir verdere studies. Afsluitend, is hoofstuk ses ń bespreking van hoe enige nuwe groeiplek indeks modelle die huidige beplannings protokol kan beïnvloed.
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Galijasevic, Amar, and Josef Tegbaru. "Can IPO first day returns be predicted? A multiple linear regression analysis." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254293.
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During the last three years the Swedish stock market has showed a strong upwards movement from the lows of 2016. At the same time the IPO activity has been large and a lot of the offerings have had a positive return during the first day of trading in the market. The goal of this study is to analyze if there is any particular IPO specific data that has a correlation with the first day return and if it can be used to predict the first day return for future IPO’s. If any regressors were shown to have correlation with the first day return, the goal is also to find a subset of regressors with even higher predictability. Then to classify which regressors show the highest correlation with a large positive return. The method which has been used is a multiple linear regression with IPO-data from the period 2017-2018. The results from the study imply that none of the chosen regressors show any significant correlation with the first day return. It is a complicated process which might be difficult to simplify and quantify into a regression model, but further studies are needed to draw a conclusion if there are any other qualitative factors which correlate with the first day return.Under de senaste tre åren har den svenska aktiemarknaden visat en kraftigt uppåtgående rörelse från de låga nivåerna 2016. Samtidigt har det varit hög IPO-aktivitet, där många noteringar har haft en positiv avkastning under den första handelsdagen. Målet med denna studie är att analysera om det finns särskilda IPO-specifika faktorer som påvisar samband med avkastningen från första handelsdagen och om det kan användas för att förutsäga utvecklingen under första handelsdagen för framtida noteringar. Om regressorerna visade korrelation är målet sedan att ta fram de bästa av dessa för att se om det ökar modellens säkerhet. Vidare var det av intresse att visa vilka regressorer som korrelerar med en positiv avkastning. Metoden som användes var en multipel linjär regression med historisk data från perioden 2017-2018. Studiens resultat visar att ingen av de valda regressorerna har någon signifikant korrelation med avkastningen under första handelsdagen. Börsintroduktioner är komplicerade processer som kan vara svåra att förenkla och kvantifiera i en regressionsmodell, men ytterligare studier behövs för att dra en slutsats om det finns andra kvalitativa faktorer som kan förklara utvecklingen under första handelsdagen.
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Basha, Elizabeth (Elizabeth Ann). "In-situ prediction on sensor networks using distributed multiple linear regression models." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/60096.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student submitted PDF version of thesis.
Includes bibliographical references (p. 199-208).
Within sensor networks for environmental monitoring, a class of problems exists that requires in-situ control and modeling. In this thesis, we provide a solution to these problems, enabling model-driven computation where complex models are replaced by in-situ sensing and communication. These prediction models utilize low-computation, low-communication, and distributed algorithms suited to autonomous operation and multiple applications. We achieve this through development of new algorithms that enable distributed computation of the pseudo inverse of a matrix on a sensor network, thereby enabling a wide range of prediction methods. We apply these models to three different application areas: (1) river flooding for early warning, (2) solar recharging current for power management, and (3) job congestion prediction on multi-function device networks for achieving quality of service. Additionally, we use these applications to explore other aspects of sensor networks: river flooding to design a predictive environmental monitoring sensor network, solar current to develop a dynamic version of the model for better fault tolerance, and job congestion to explore modeling multi-function device networks. For each, we comprehensively tested the full solutions. We implemented the river flood prediction and solar current prediction solutions on two different sensor network platforms with full field deployments; we had a final test of over 5 weeks operation for both. Overall, we achieve the following contributions: (1) distributed algorithms for computing a matrix pseudoinverse and multiple linear regression model on a sensor network, (2) three applications of these algorithms with associated field experiments demonstrating their versatility, (3) a sensor network architecture and implementation for river flood prediction as well as other applications requiring real-time data and a low node count to geographic area ratio, and (4) a MFD simulator predicting and resolving congestion.
by Elizabeth Ann Basha.
Ph.D.
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Filho, Nicolino Trompieri. "ANÃLISE DOS RESULTADOS DA AVALIAÃÃO DO SAEB/2003 VIA REGRESSÃO LINEAR MÃLTIPLA." Universidade Federal do CearÃ, 2007. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=1993.
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nÃo hÃO presente estudo teve como objetivo identificar nos resultados do SAEB/2003, no CearÃ, um modelo multilinear com variÃveis que garantam o maior grau de explicaÃÃo do rendimento em matemÃtica nos testes aplicados nas amostras de 4Â sÃrie da escola pÃblica; 4Â sÃrie da escola particular; 8Â sÃrie da escola pÃblica e 8Â sÃrie da escola particular. Tomando-se, entre as variÃveis do diretor, do professor, do aluno e das condiÃÃes fÃsicas da escola, as variÃveis que se relacionavam significativamente com o rendimento no teste de matemÃtica em cada uma das amostraS, com os recursos do software SPSS (Statical Package for the Social Sciences), uma regressÃo linear em cada amostra, com o mÃtodo âstepwareâ. Obtiveram-se quatro modelos lineares mÃltiplos com variÃveis que permitem um maior grau de explicaÃÃo do rendimento no teste em matemÃtica em cada uma das amostras. Conclui-se que a anÃlise desse tipo permite a formulaÃÃo de polÃticas pÃblicas capazes de superar a busca da melhoria do ensino por intervenÃÃes pontuais.
This study had as its objective the identification in the results of SAEB/2003, here in CearÃ, of a multilinear model with variables that gave a greater degree of explaination for the results in mathematics of tests given in the randomic sample of the fourth years students in public schools, the fourth year students in private schools, the eight year students in public schools and the eight year students in private schools. The following variables were taken into account: the director, the teacher, the student, the physical state of the school as variables that had significant relevance with the results of the tests in mathematics in each one of the samples, using the resources of the software SPSS (Statical Package for the School Sciences), a linear regression in each sample, using the method "stepware". Four multilinear models with variables were obtained that permitted a greater degree of explaination for the results of the mathematic tests in each sample. The study concluded affirming that an analysis of this type permits the formulation of public politics capable of overcoming the search for better forms of teaching with punctual interventions.
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Lin, Xiaojun. "Multiple Random Slope and Fixed Intercept Linear Regression Models for Pavement Condition Forecasting." University of Toledo / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1430364217.
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Denés, August, and Martin Lindblom. "Determining Important Factors for Profiability in Dietary Supplement Retailing by Multiple Linear Regression." Thesis, KTH, Matematisk statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188995.
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This thesis in applied statistics and industrial economics examined which factors and strategies that had a statistically significant impact on profitability, within the business to consumer dietary supplement market. The data this thesis was based on consisted of several annual reports from the year 2011 to 2015ånd other strategic information. The data included 19 different dietary supplement retailers on the Swedish market. In order to establish which factors had a significant impact on profitability, a linear regression was used. The result was an identified linear relationship between Operating Margin and the covariates Solidity, Average Salary, Only Own Brand, Free Returns, Student Discounts and Chat. A market analysis was then performed using Porter's five forces and a PEST analysis. The analysis concluded that the market is attractive but there are a few uncertainties surrounding the future development of the dietary supplement retailing market.Det här kandidatexamensarbetet i tillämpad statistik och industriell ekonomi undersökte vilka faktorer och strategier som hade en statistiskt signifikant påverkan på lönsamhet, inom kosttillskottsåterförsäljning på den svenska konsumentmarknaden. Data som rapporten är baserad på kom ifrån flertalet årsredovisningar mellan åren 2011 och 2015 samt annan strategisk information. Studien inkluderade 19 olika företag på den svenska kosttillskottsåterförsäljningsmarknaden. För att identifiera de påverkande faktorerna tillämpades linjär regression. Resultat visade att det finns ett linjärt samband mellan Rörelsemarginal och kovariaten Soliditet, Snittlön, Endast Eget Märke, Fria Returer, Studentrabatt och Chatt. Sedan utfördes en marknadsanalys med hjälp av Porters's femkraftsmodell samt PEST-analys. Anslysen fastslog att marknaden är attraktiv, men det finns några osäkerheter rörande den framtida utvecklingen på kosttillskottsåterförsäljningsmarknaden.
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Leimkuhler, Matthew Pancoast. "Linear stability analysis of circular jets : integer, fractional, and multiple mode excitation /." Thesis, This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-06082009-170937/.
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Knies, Alberto Eduardo. "Estimativa do escoamento superficial em diferentes níveis de dossel vegetativo e cobertura do solo." Universidade Federal de Santa Maria, 2014. http://repositorio.ufsm.br/handle/1/3612.
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Conselho Nacional de Desenvolvimento Científico e TecnológicoThe soil tillage systems modify its water balance and for the correct irrigation management is fundamental to determining the runoff and effective rainfall, which helps to maximize the use of rainwater and minimizes the use of supplemental irrigation. The objective of this study was to determine, model and estimate the runoff and the effective rainfall during the development cycle of the common black bean and maize in soil with and without straw on the surface, in different land slope and rainfall intensities simulated, using the field experiments, multivariate equations, the Curve Number Method (CN) and the SIMDualKc Model. Two experiments were conducted in the field with crops of black beans and maize, where different intensities of simulated rainfall (35, 70 and 105 mm h-1) were applied at different times of the crop cycle (soil cover of 0, 28, 63 and 100% by the canopy beans; 0, 30, 72 and 100% by canopy of maize) and distinct land slope (1, 5 and 10%) in soil without and with (5 Mg ha-1) of oat straw on the surface. The runoff values observed were compared with those estimated by the CN method, suggesting new values of CN to improve the estimate. From the set of data collected from the field analysis of multiple linear regression to estimate runoff and simulations with SIMDualKc model to estimate runoff and effective rainfall were performed. The start time of the runoff, constant runoff rate, total runoff and the percentage of runoff in relation to the volume of rain were little influenced by the crops of beans and maize. Reductions in runoff were provided by the straw on the soil surface within 45 and 48% for the crops beans and maize, respectively. The CN method for the bean crop underestimated runoff by up to 10% for the soil without straw on the surface, and overestimated by up to 17% for the soil with straw. For maize, the method overestimated the runoff by up 32.4% in soil with straw and 12% in soil without straw. To improve estimation the CN, new values are proposed for CN, considering the crop, the presence or absence of straw on soil surface and intensity rain. The use of multiple linear regression analyzes indicated that the volume of precipitation (R2=0.52) and soil cover by straw (R2=0.18) are the variables with the greatest influence on runoff. Four multiple equations were generated, and the equation 2, whose input parameters are the volume of rain and amount of litter on the soil surface, was presented the best estimate of the runoff of a data set than the one that gave its origin. The SIMDualKc Model requires adjustments to estimate runoff and effective rainfall during the crop cycle of beans and maize, so consider the benefits of straw on the soil surface in reducing runoff. Thus, the suggested value of CN (CN=75) was changed to 71 and 87 to the black bean crop, and 56 and 79 for the maize crop for the soil with and without straw on the surface, respectively.
Os sistemas de manejo do solo modificam o seu balanço hídrico e para o correto manejo da irrigação é de fundamental importância a determinação do escoamento superficial e da chuva efetiva, o que contribui para maximizar o uso da água das chuvas e minimiza a utilização de irrigação suplementar. O objetivo do presente trabalho foi determinar, modelar e estimar o escoamento superficial e a chuva efetiva durante o ciclo de desenvolvimento das culturas do feijão e milho, cultivados em solo com e sem palha na superfície, em diferentes declividade do terreno e intensidades de chuvas simuladas, utilizando experimentos a campo, equações multivariadas, o método Curva Número (CN) e o modelo SIMDualKc. Foram realizados dois experimentos à campo, com as culturas do feijão e milho, em que foram aplicadas diferentes intensidades de chuvas simuladas (35, 70 e 105 mm h-1), em diferentes momentos do ciclo das culturas (cobertura do solo de 0, 28, 63 e 100% pelo dossel vegetativo do feijão; 0, 30, 72 e 100% pelo dossel vegetativo do milho) e distintas declividade do terreno (1, 5 e 10%), em solo sem e com (5 Mg ha-1) palha de aveia preta na superfície. Os valores de escoamento superficial observados foram comparados com os estimados pelo método CN, sugerindo-se novos valores de CN para melhorar a estimativa. A partir do conjunto de dados coletados a campo, foram realizadas análises de regressão linear múltiplas para a estimativa do escoamento superficial e, simulações com o modelo SIMDualKc para estimativa do escoamento superficial e da chuva efetiva. O tempo de início do escoamento, a taxa constante de escoamento, o escoamento total e a porcentagem de escoamento em relação ao volume da chuva foram pouco influenciados pelo crescimento do dossel vegetativo das plantas de feijão e milho. Reduções no escoamento superficial foram proporcionadas pela presença de palha na superfície do solo, em até 45 e 48% para as culturas do feijão e milho, respectivamente. O método CN para a cultura do feijão subestimou o escoamento superficial em até 10% para o solo sem palha na superfície e, superestimou em até 17% para o solo com palha. Para a cultura do milho, o método CN superestimou o escoamento superficial em até 32,4% no solo com palha e 12% no solo sem palha. Para melhorar a estimativa do método CN, foram propostos novos valores de CN, considerando a cultura, a presença ou não de palha na superfície do solo e a intensidade da chuva. A utilização de análises de regressão linear múltiplas indicaram que o volume da chuva (R2=0,52) e a cobertura do solo por palha (R2=0,18) são as variáveis com maior influência sobre o escoamento superficial. Foram geradas quatro equações múltiplas, sendo que a equação 2, cujos parâmetros de entrada são o volume da chuva e quantidade de palha na superfície do solo, foi a que apresentou a melhor estimativa do escoamento superficial de um conjunto de dados diferente daquele que lhe deu origem. O modelo SIMDualKc necessita de ajustes para estimar o escoamento superficial e a chuva efetiva durante o ciclo das culturas de feijão e milho, de modo que considere os benefícios da palha na superfície do solo na redução do escoamento superficial. Desta forma, o valor sugerido de CN (CN=75) foi alterado para 71 e 87 para a cultura do feijão e, 56 e 79 para a cultura do milho, para o solo com e sem palha na superfície, respectivamente.
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Kareflod, Michaela, and Jennifer Ljungquist. "A Study of Hot el Occupancy : Using Multiple Linear Regression and Market Strategy Analysis." Thesis, KTH, Matematisk statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189017.
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This paper is based on collaboration between a company called StayAt HotelApart AB and two KTH students. It examines which factors that are influencing the hotel’s occupancy and how this may be increased by enhancing the market strategy. The aim is to provide a foundation for strategy development to the company. The study is performed by connecting applied mathematics with industrial management. The mathematical part is based on a multiple linear regression on occupancy with historical data from 2011 to 2016 mainly collected from StayAt. The analysis of the market strategy is performed by means of the mathematical results and by using two marketing models, SWOT analysis and 4P’s. The result shows that relative price, weather, high- and low season for the hotel, months on market, occupancy for the competitive set, location and market shares are significant factors influencing the hotel’s occupancy. The main recommendations concluded from the analysis of the market strategy are to put effort on digitalisation, visualising the brand, publications, CSR initiatives, exploiting existing resources and carefully considering timing of marketing.Den här uppsatsen baseras på ett samarbete mellan företaget StayAt HotelApart AB och två KTH- studenter. Den utvärderar vilka faktorer som påverkar hotellets beläggning och hur denna kan öka genom en förbättrad marknadsstrategi. Syftet är att leverera en grund för strategiutveckling till företaget. Studien är genomförd genom att sammankoppla tillämpad matematik med industriell ekonomi. Den matematiska delen baseras på en regressionsanalys av hotellets beläggning med historisk data från 2011 till 2016 som främst är försedd av StayAt. Analysen av marknadsstrategin är genomförd med hjälp av de matematiska resultaten samt genom att applicera två modeller inom marknadsföring, SWOT analys och 4P. Resultaten visar att relativt pris, väder, hög- och lågsäsong för hotellet, månader på marknaden, beläggning för konkurrenter, läge och marknadsandelar är signifikanta faktorer som påverkar hotellets beläggning. De primära rekommendationerna som tagits fram utifrån analysen av marknadsstrategin är att lägga resurser på digitalisering, publikationer och CSR initiativ, att visualisera varumärket, utnyttja existerande resurser samt att grundligt överlägga timing av marknadsföring
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Peraça, Maria da Graça Teixeira. "Modelos para estimativa do grau de saturação do concreto mediante variáveis ambientais que influenciam na sua variação." reponame:Repositório Institucional da FURG, 2009. http://repositorio.furg.br/handle/1/3436.
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Dissertação(mestrado) - Universidade Federal do Rio Grande, Programa de Pós-Graduação em Engenharia Oceânica, Escola de Engenharia, 2009.Submitted by Lilian M. Silva (lilianmadeirasilva@hotmail.com) on 2013-04-22T19:51:54Z No. of bitstreams: 1 Modelos para estimativa do Grau de Saturação do concreto mediante Variáveis Ambientais que influenciam na sua variação.pdf: 2786682 bytes, checksum: df174dab02a19756db94fc47c6bb021d (MD5)
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Nas engenharias, é fundamental estimar o tempo de vida útil das estruturas construídas, o que neste trabalho significa o tempo que os íons cloretos levam para atingirem a armadura do concreto. Um dos coeficientes que influenciam na vida útil do concreto é o de difusão, sendo este diretamente influenciado pelo grau de saturação (GS) do concreto. Recentes estudos levaram ao desenvolvimento de um método de medição do GS. Embora esse método seja eficiente, ainda assim há um grande desperdício de tempo e dinheiro em utilizá-lo. O objetivo deste trabalho é reduzir estes custos calculando uma boa aproximação para o valor do GS com modelos matemáticos que estimem o seu valor através de variáveis ambientais que influenciam na sua variação. As variáveis analisadas nesta pesquisa, são: pressão atmosférica,temperatura do ar seco, temperatura máxima, temperatura mínima, taxa de evaporação interna (Pichê), taxa de precipitação, umidade relativa, insolação, visibilidade, nebulosidade e taxa de evaporação externa. Todas foram analisadas e comparadas estatisticamente com medidas do GS obtidas durante quatro anos de medições semanais, para diferentes famílias de concreto. Com essas análises, pode-se medir a relação entre estes dados verificando que os fatores mais influentes no GS são, temperatura máxima e umidade relativa. Após a verificação desse resultado, foram elaborados modelos estatísticos, para que, através dos dados ambientais, cedidos pelo banco de dados meteorológicos, se possam calcular, sem desperdício de tempo e dinheiro, as médias aproximadas do GS para cada estação sazonal da região sul do Brasil, garantindo assim uma melhor estimativa do tempo de vida útil em estruturas de concreto.
In engineering, it is fundamental to estimate the life-cycle of built structures, which in this study means the period of time required for chlorides to reach the concrete reinforcement. One of the coefficients that affect the life-cycle of concrete is the diffusion, which is directly influenced by the saturation degree (SD) of concrete. Recent studies have led to the development of a measurement method for the SD. Although this method is efficient, there is still waste of time and money when it is used. The objective of this study is to reduce costs by calculating a good approximation for the SD value with mathematical models that predict its value through environmental variables that affect its variation. The variables analysed in the study are: atmospheric pressure, temperature of the dry air, maximum temperature, minimum temperature, internal evaporation rate (Pichê), precipitation rate, relative humidity, insolation, visibility, cloudiness and external evaporation rate. All of them were statistically analysed and compared with measurements of SD obtained during four years of weekly assessments for different families of concrete. By considering these analyses, the relationship among these data can be measured and it can be verified that the most influent variables affecting the SD are the maximum temperature and the relative humidity. After verifying this result, statistical models were developed aiming to calculate, based on the environmental data provided by the meteorological database and without waste of time and money, the approximate averages of SD for each seasonal station of the south region of Brazil, thus providing a better estimative of life-cycle for concrete structures.
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Palmgren, Elin, and Natasha Nanakorn. "The Impact of Macroeconomic Variables on Stock Return in Different Industries - A Multiple Linear Regression." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254204.
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Macroeconomics constitute a central part of fundamental analysis of stock markets and consequently the relationship between macroeconomic variables and stock markets is far from questioned. However, there is no general consensus regarding neither the extent of this relationship nor whether the relationship varies amongst industries. The aim of this thesis is therefore to determine the macroeconomic variables most important in explaining variations in stock return within two separate industries and furthermore the share of these variations solely accounted for by macroeconomic variables. To this end, a multiple linear regression approach is used and Nasdaq indexes OMX Stockholm Industrial Goods & Services and OMX Stockholm Banks are used as proxies for the two selected industries. The final result of this analysis is that the variables repo rate, SEK/EUR exchange rate, consumer expectations, oil price, GDP, money supply and inflation are statistically significant in explaining stock return within industrial goods and services whilst SEK/USD exchange rate, SEK/EUR exchange rate, oil price, GDP, money supply and inflation are statistically significant in explaining stock return within the banking industry. The analysis of the extent of the impact of these variables on stock return is, however, deemed inconclusive due to time dependencies amongst the variables.Makroekonomi utgör en central del av fundamental analys av aktiemarknaden och följaktligen är förhållandet mellan makroekonomiska variabler och aktiemarknaden snarare väl etablerat än ifrågasatt. Emellertid saknas rådande konsensus om såväl omfattningen av detta förhållande som huruvida förhållandet skiljer sig mellan olika branscher. Syftet med detta kandidatexamensarbete är därför att fastställa de makroekonomiska variabler som är mest avgörande för variationen i aktieavkastning inom två skilda branscher samt andelen av dessa variationer som kan hänföras till just makroekonomiska variabler. I detta syfte tillämpas en multipel linjär regression och två Nasdaqindex - OMX Stockholm Industrial Goods & Services samt OMX Stockholm Banks - tillåts approximera de två utvalda branscherna. Det slutgiltiga resultatet av denna analys är att variablerna reporänta, växelkurs SEK/EUR, konsumentförväntningar, oljepris, BNP, penningmängd och inflation är statistiskt signifikanta för aktieavkastning inom industrin, medan växelkurs SEK/EUR samt SEK/USD, oljepris, BNP, penningmängd och inflation är statistiskt signifikanta för aktieavkastning inom bankbranschen. Analysen av omfattningen av dessa makroekonomiska variablers påverkan på aktieavkastning når emellertid ingen slutsats, vilket anses kunna hänföras till tidsberoende hos variablerna.
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Buzatoiu, Roxana. "Long Term Forecasting of Industrial Electricity Consumption Data With GRU, LSTM and Multiple Linear Regression." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-289632.
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Accurate long-term energy consumption forecasting of industrial entities is of interest to distribution companies as it can potentially help reduce their churn and offer support in decision making when hedging. This thesis work presents different methods to forecast the energy consumption for industrial entities over a long time prediction horizon of 1 year. Notably, it includes experimentations with two variants of the Recurrent Neural Networks, namely Gated Recurrent Unit (GRU) and Long-Short-Term-Memory (LSTM). Their performance is compared against traditional approaches namely Multiple Linear Regression (MLR) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Further on, the investigation focuses on tailoring the Recurrent Neural Network model to improve the performance. The experiments focus on the impact of different model architectures. Secondly, it focuses on testing the effect of time-related feature selection as an additional input to the Recurrent Neural Network (RNN) networks. Specifically, it explored how traditional methods such as Exploratory Data Analysis, Autocorrelation, and Partial Autocorrelation Functions Plots can contribute to the performance of RNN model. The current work shows through an empirical study on three industrial datasets that GRU architecture is a powerful method for the long-term forecasting task which outperforms LSTM on certain scenarios. In comparison to the MLR model, the RNN achieved a reduction in the RMSE between 5% up to to 10%. The most important findings include: (i) GRU architecture outperforms LSTM on industrial energy consumption datasets when compared against a lower number of hidden units. Also, GRU outperforms LSTM on certain datasets, regardless of the choice units number; (ii) RNN variants yield a better accuracy than statistical or regression models; (iii) using ACF and PACF as dicovery tools in the feature selection process is unconclusive and unefficient when aiming for a general model; (iv) using deterministic features (such as day of the year, day of the month) has limited effects on improving the deep learning model’s performance.Noggranna långsiktiga energiprognosprognoser för industriella enheter är av intresse för distributionsföretag eftersom det potentiellt kan bidra till att minska deras churn och erbjuda stöd i beslutsfattandet vid säkring. Detta avhandlingsarbete presenterar olika metoder för att prognostisera energiförbrukningen för industriella enheter under en lång tids förutsägelsehorisont på 1 år. I synnerhet inkluderar det experiment med två varianter av de återkommande neurala nätverken, nämligen GRU och LSTM. Deras prestanda jämförs med traditionella metoder, nämligen MLR och SARIMA. Vidare fokuserar undersökningen på att skräddarsy modellen för återkommande neurala nätverk för att förbättra prestanda. Experimenten fokuserar på effekterna av olika modellarkitekturer. För det andra fokuserar den på att testa effekten av tidsrelaterat funktionsval som en extra ingång till RNN -nätverk. Specifikt undersökte den hur traditionella metoder som Exploratory Data Analysis, Autocorrelation och Partial Autocorrelation Funtions Plots kan bidra till prestanda för RNN -modellen. Det aktuella arbetet visar genom en empirisk studie av tre industriella datamängder att GRU -arkitektur är en kraftfull metod för den långsiktiga prognosuppgiften som överträffar ac LSTM på vissa scenarier. Jämfört med MLR -modellen uppnådde RNN en minskning av RMSE mellan 5 % upp till 10 %. De viktigaste resultaten inkluderar: (i) GRU -arkitekturen överträffar LSTM på datauppsättningar för industriell energiförbrukning jämfört med ett lägre antal dolda enheter. GRU överträffar också LSTM på vissa datauppsättningar, oavsett antalet valenheter; (ii) RNN -varianter ger bättre noggrannhet än statistiska modeller eller regressionsmodeller; (iii) att använda ACF och PACF som verktyg för upptäckt i funktionsvalsprocessen är otydligt och ineffektivt när man siktar på en allmän modell; (iv) att använda deterministiska funktioner (t.ex. årets dag, månadsdagen) har begränsade effekter på att förbättra djupinlärningsmodellens prestanda.
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Habgood, Helen Leslie. "Estimation of browse biomass production of Salix SPP. and Betula blandulosa using multiple linear regression." Thesis, University of British Columbia, 1985. http://hdl.handle.net/2429/24676.
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Browse biomass production of Salix spp. and Betula glandulosa on a wetland in central British Columbia is estimated. Based on an extensive review of much of the literature pertaining to shrub biomass and shrub density estimation, a technique combining regression estimates of average stem biomass with a density estimate obtained using the corrected point distance method was applied. It was found that the best regression relationships were obtained using natural logarithmic transformations of the dimension and biomass variables. It was possible to obtain acceptable biomass equations for the four Salix species encountered without differentiating between the species. More accurate predictions of biomass were achieved using site specific equations and equations based on pooled site data than with general equations. It was concluded that the value of the approach taken is limited if site specific equations are required because of the considerable time required for sample collection and preparation.Forestry, Faculty of
Graduate
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Laird, Daniel T. "Logistics Regression Model on Antenna Control Unit Autotracking Mode." International Foundation for Telemetering, 2015. http://hdl.handle.net/10150/596414.
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ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NVOver the past several years DoD imposed constraints on test deliverables, requiring objective measures of test results, i.e., statistically defensible test and evaluation (SDT&E) methods and results. These constraints force testers to employ statistical hypotheses, analyses and modeling to assess test results objectively, i.e., based on statistical metrics, analytical methods, probability of confidence complemented by, rather than solely on expertise, which is too subjective. In this and companion papers we discuss methods of objectifying testing. We employ an earth coordinate model and statistical modeling of telemetry (TM) tracking antenna employing time-space position information (TSPI) and derived statistical measures for tracking-error and auto-tracking mode. Test data were statistically analyzed via analysis of covariance (ANCOVA) which revealed that the antenna control unit (ACU) under test (AUT) does not track statistically identically, nor as practically or efficiently in C-band while receiving data carriers in both S- and C-bands. The conclusions of this paper add support to that hypothesis. In this third of three papers we use data from a range test, but make no reference to the systems under test as the purpose of this paper is to present an example of tools useful for employing a SDT&E methodology.
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Goicoechea, Saioa, and Patricia López. "Modeling the air change rate in a naturally ventilated historical church : MultipleLinear Regression analysis." Thesis, Högskolan i Gävle, Akademin för teknik och miljö, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-13640.
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In this thesis the air infiltration through the envelope of a naturally ventilated stone church located in Bergby (Gävle, Sweden) is studied. The project is focused on Multiple Linear Regression (MLR) modeling the air change rate (ACH) inside the church hall and studying the factors (stack effect and wind effect) that influence the air infiltration. The weather parameters outside the building were recorded in a weather station and the properties of the air inside the church was analyzed with different methods. Infrared thermography techniques and thermistors were used to measure the temperature inside, the tracer gas method to measure the ACH and the blower door technique to measure the tightness of the building envelope. In order to know the pressure coefficients on the church envelope a physical model of the building was studied in a wind tunnel. Firstly, only the values obtained from the weather station were used to calculate the predictors of ACH and see which parameter influence more on its variation: temperature difference (∆T) indicating the stack effect; and wind speed (WS), the component of wind speed perpendicular to the long-side facades of the church (WS90) and their square values (WS2 and WS902) indicating the wind effect. The data obtained in the wind tunnel were later used to do the MLR study with new predictors for indicating wind effect (∆Cp∙WS, ∆Cp∙WS2, ∆CpOUT-IN·A∙WS, ∆CpOUT-IN·A∙WS2, ∆CpC-H∙WS, ∆CpC-H∙WS2). Better prediction of ACH was obtained with the square of the wind speed (WS2) instead of the magnitude itself (WS). However, the latter (WS) provided better results than the regression with the magnitude of the perpendicular component of the wind (WS90). Although wind speed influences in ACH, it alone seems to be a very poor predictor of ACH since has a negative correlation with ΔT when the data under study include both day and night. However when high wind speed are detected it has quite strong influence. The most significant predictions of ACR were attained with the combined predictors ∆T & WS and ∆T & ∆CpOUT-IN·A∙WS2. The main conclusion taken from the MLR analysis is that the stack effect is the most significant factor influencing the ACH inside the church hall. This leads to suggest that an effective way of reducing ACH could be sealing the floor and ceiling of the church because from those areas the air infiltration has big influence on the ACH inside the church hall, and more in this case that have been noted that the floor is very leaky. Although different assumptions have been done during the analyses that contribute to make the predictions deviate from reality, at the end it would be possible to asses that MLR can be a useful tool for analyzing the relative importance of the driving forces for ACR in churches and similar buildings, as long as the included predictors not are too mutually correlated, and that attained models that are statistically significant also are physically realistic.Church project
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Patikorn, Thanaporn. "Improvements on Trained Across Multiple Experiments (TAME), a New Method for Treatment Effect Detection." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-theses/792.
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One of my previous works introduced a new data mining technique to analyze multiple experiments called TAME: Trained Across Multiple Experiments. TAME detects treatment effects of a randomized controlled experiment by utilizing data from outside of the experiment of interest. TAME with linear regression showed promising result; in all simulated scenarios, TAME was at least as good as a standard method, ANOVA, and was significantly better than ANOVA in certain scenarios. In this work, I further investigated and improved TAME by altering how TAME assembles data and creates subject models. I found that mean-centering “prior� data and treating each experiment as equally important allow TAME to detect treatment effects better. In addition, we did not find Random Forest to be compatible with TAME.
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Tong, Fan. "Capacity demand and climate in Ekerö : Development of tool to predict capacity demand underuncertainty of climate effects." Thesis, KTH, Elektroteknisk teori och konstruktion, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-152522.
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The load forecasting has become an important role in the operation of power system, and several models by using different techniques have been applied to solve these problems. In the literature, the linear regression models are considered as a traditional approach to predict power consumption, and more recently, the artificial neural network (ANN) models have received more attention for a great number of successful and practical applications. This report introduces both linear regression and ANN models to predict the power consumption for Fortum in Ekerö. The characteristics of power consumption of different kinds of consumers are analyzed, together with the effects of weather parameters to power consumption. Further, based on the gained information, the numerical models of load forecasting are built and tested by the historical data. The predictions of power consumption are focus on three cases separately: total power consumption in one year, daily peak power consumption during winter and hourly power consumption. The processes of development of the models will be described, such as the choice of the variables, the transformations of the variables, the structure of the models and the training cases of ANN model. In addition, two linear regression models will be built according to the number of input variables. They are simple linear regression with one input variable and multiple linear regression with several input variables. Comparison between the linear regression and ANN models will be carried out. In the end, it finds out that the linear regression obtains better results for all the cases in Ekerö. Especially, the simple linear regression outperforms in prediction of total power consumption in one year, and the multiple linear regression is better in prediction of daily peak load during the winter.
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Högbom, Johannes, and August Regnell. "Analysis of Performance Measures affecting the economic success on the PGA Tour using multiple linear regression." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-275678.
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This bachelor thesis examined the relationship between performance measures and prize money earnings on the PGA Tour. Using regression analysis and data from seasons 2004 through 2019 retrieved from the PGA Tour website this thesis examined if prize money could be predicted. Starting with 102 covariates, comprehensibly covering all aspects of the game, the model was reduced to 13 with Driving Distance being most prominent, favouring simplicity resulting in an R2Adjusted of 0.6918. The final model was discussed in regard to relevance, reliability and usability. This thesis further analysed how the entry of ShotLink, the technology responsible for the vast statistical database surrounding the PGA Tour, have affected golf in general and the PGA Tour in particular. Analysis regarding how ShotLink affected golf on different levels, both for players as well as other stakeholders, where conducted. These show developments on multiple levels; on how statistics are used, golf related technologies, broadcasts, betting market, and both amateur and PGA Tour playing golf players. The analysis of the latter, using statistics from the PGA Tour website, showed a significant improvement in scoring average since ShotLinks inception.Detta kandidatexamensarbete undersökte relationen mellan prestationsmått och prispengar på PGA Touren. Genom regressionsanalys och data från säsongerna 2004 till och med 2019 hämtat från PGA Tourens hemsida undersökte detta arbete om prispengar kunde predikteras. Startandes med 102 kovariat, täckandes alla aspekter av spelet, reducerades sedan modellen till 13 med Utslags Distans mest framträdande, i förmån för simplicitet och resulterande i ett R2Adj på 0.6918. Den slutliga modellen diskuterades sedan gällande relevans, reliabilitet och användbarhet. Vidare analyserar detta arbete hur ShotLinks entré, tekniken ansvarig för den omfattande statistikdatabasen som omger PGA Touren, har påverkat golf generellt och PGA Touren specifikt. Analyser gällande hur ShotLink har påverkat golf på olika nivåer, både för spelare och andra intressenter, genomfördes. Dessa visar utvecklingar på flera fronter; hur statistik används, golfrelaterade teknologier, mediasändningar, bettingmarknad samt både för amatörspelare och spelare på PGA Touren. Den senare analysen, genom användande av statistik från PGA Tourens hemsida, visade på en signifikant förbättring i genomsnittsscore sedan ShotLink infördes.
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Wijkström, Oscar, and Sofia Öhman. "Macroeconomic factors that correlate with the performance of IndustrialTransportation Companies : A study using multiple linear regression." Thesis, KTH, Matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-209792.
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This thesis in Applied Mathematics and Industrial Economics examines which macroeconomic factors, related to the business cycle, that correlate with the performance of Industrial Transportation Companies. The data for the thesis is collected with the help of Nordea and from reports of each variable. The observations stretch from January 2007 to December 2016, a ten-year period. The data is monthly, hence there are 120 observed data points for each variable. A linear regression analysis was performed with the result that there is a linear relationship between the performance of the Industrial Transportation Companies and the variables Price per MWh, Fuel Price, Exchange rate USD-SEK, Exchange rate EUR-SEK, Manpower Employment Outlook Survey, Repo Rate, OECD Index Sweden, and Purchasing Manager’s Index. Further analysis of the Swedish and international economic history in the last decade was conducted which concluded why said variables were significant.Det här kandidatexamensarbetet i Tillämpad Matematik och Industriell Ekonomi undersöker vilka konjunkturcykelsrelaterade makroekonomiska faktorer som korrelerar med utvecklingen av Industriella Transportmedelsföretag. Datan för arbetet är sammanställd med hjälp av Nordea och från olika rapporter av vardera variabel. Observationerna sträcker sig från Januari 2007 till December 2016, en tioårsperiod. Datan är månatlig, vilket betyder att 120 datapunkter är observerade för vardera variabel. En linjär regressionsanalys tillämpades med resultatet att det finns ett linjärt samband mellan utvecklingen av industriella transportmedelsföretag och kovariaterna Pris per MWh, Bensinpris, Valutakurs USD-SEK, Valutakurs EUR-SEK, Manpower Arbetsmarknadsbarometer, Reporänta, OECD Index Sweden och Inköpschefsindex. Vidare analys av den svenska och internationella ekonomiska historian för det senaste årtiondet genomfördes vilken drog slutsatsen kring varför de nämnda variablerna var signifikanta.
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Brandner, Hanna. "Idenitfying the Influential Factors of the Temporal Variation of Water Consumption : A Case Study using Multiple Linear Regression Analysis." Thesis, KTH, Vattendragsteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-192650.
Full textAbstract:
This thesis is a part of the water development project conducted by Svenskt Vatten, which is the Swedish Water and Wastewater Association (SWWA) as well as Tyréns, a consultancy company with offices based in Stockholm, Sweden. Prior to this thesis work, a quality assessment was conducted for some of the locations provided by municipalities in Sweden. This thesis builds upon the revised water consumption data, and also continues to work with validating and modifying the water measurement data in order to proceed with the next step of the water development project, which is to identify any trends in the temporal variation of water consumption. The main objective of this thesis work is to investigate the influence of climatic, time-related and categorical factors on water consumption data collected for different regions in Sweden, and includes a number of different sectors such as residential, industrial and agricultural water user sectors. For the analysis of data, spectral analysis and sinusoidal modelling will be applied in order to find the periodicity of the data, and then simulate the fitted sinusoidal equation to the observed water consumption data for the hourly interval period. Multiple linear regression analysis is then used to assess what independent variables such as climate, time-related and categorical variables can explain the variation in water consumption over hourly and daily periods of time. Spectral analysis identifies high peaks in the spectral density of the data at 12 and 24 hour cycles, for the hourly water consumption data. For the total daily consumption of water, there is a peak at 7 days, which clarifies that there is a weekly pattern occurring throughout the year. The results from the simple linear regression analysis, where the linear relationship between temperature and water consumption was determined, reveals that the water consumption tends to increase within an increasing temperature, where in Lönashult, Alvesta municipality the water demand increased by 5.5% with every 2 ºC rise in temperature, at a threshold of 12 ºC. For Kalix municipality the three areas selected have around 1-2 % increase in water demand with every 2 ºC rise in temperature for the period of May to December. In Gothenburg, areas that were mixed villa areas or areas with summer homes there was a rise of around 2-12 % in water demand, however areas that are situated in the inner city Gothenburg, or that have majority student housing, the water consumption tends to decrease by 2-7% in water demand with every 2 ºC rise in temperature, with a threshold of 12 ºC. In multiple regression analysis, the hourly water consumption results in adjusted R2 values were in the range from 0.58 to 0.87 (58-87%) for the best model approach and therefore has a significant relationship between water consumption and the explanatory variables chosen for this study. For the daily water consumption, the adjusted R2 values were in the range of 0.22-0.83 (22-83%). The adjusted R2 values are lower for certain areas and can be explained by a number of factors, such as the different variables used for the daily water consumption analysis, as variables that explain more the periodicity of the data such as the sinusoidal fitted variable and hourly or night/day changes in consumption are not included. As well as this, not all independent variables such as the climate variables were available or complete for particular time periods, and also errors in the data can lead to a significantly lower R2 value.