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1
Jacobs, Mary Christine. "Regression Trees Versus Stepwise Regression." UNF Digital Commons, 1992. http://digitalcommons.unf.edu/etd/145.
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Many methods have been developed to determine the "appropriate" subset of independent variables in a multiple variable problem. Some of the methods are application specific while others have a wide range of uses. This study compares two such methods, Regression Trees and Stepwise Regression. A simulation using a known distribution is used for the comparison. In 699 out of 742 cases the Regression Tree method gave better predictors than the Stepwise Regression procedure.
2
Petrovič, Branislav. "Regresní metody odhadu vybraných charakteristik tavených sýrů v závislosti na poměru tavicích solí." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2013. http://www.nusl.cz/ntk/nusl-230946.
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This thesis deals with regression analysis of experimentally measured data of processed cheese. There is a polynomial regression used. The choice of regressors is based on Stepwise Regression and Mallows's Statistics. The estimation of the mean value is used to find the best mixture of the emulsifying salts with regards to the observed characteristic of the processed cheese. Analysis of the experiment and its results are well documented graphically.
3
Emfevid, Lovisa, and Hampus Nyquist. "Financial Risk Profiling using Logistic Regression." Thesis, KTH, Matematisk statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229821.
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As automation in the financial service industry continues to advance, online investment advice has emerged as an exciting new field. Vital to the accuracy of such service is the determination of the individual investors’ ability to bear financial risk. To do so, the statistical method of logistic regression is used. The aim of this thesis is to identify factors which are significant in determining a financial risk profile of a retail investor. In other words, the study seeks to map out the relationship between several socioeconomic- and psychometric variables to develop a predictive model able to determine the risk profile. The analysis is based on survey data from respondents living in Sweden. The main findings are that variables such as income, consumption rate, experience of a financial bear market, and various psychometric variables are significant in determining a financial risk profile.I samband med en ökad automatiseringstrend har digital investeringsrådgivning dykt upp som ett nytt fenomen. Av central betydelse är tjänstens förmåga att bedöma en investerares förmåga till att bära finansiell risk. Logistik regression tillämpas för att bedöma en icke- professionell investerares vilja att bära finansiell risk. Målet med uppsatsen är således att identifiera ett antal faktorer med signifikant förmåga till att bedöma en icke-professionell investerares riskprofil. Med andra ord, så syftar denna uppsats till att studera förmågan hos ett antal socioekonomiska- och psykometriska variabler. För att därigenom utveckla en prediktiv modell som kan skatta en individs finansiella riskprofil. Analysen genomförs med hjälp av en enkätstudie hos respondenter bosatta i Sverige. Den huvudsakliga slutsatsen är att en individs inkomst, konsumtionstakt, tidigare erfarenheter av abnorma marknadsförhållanden, och diverse psykometriska komponenter besitter en betydande förmåga till att avgöra en individs finansiella risktolerans
4
Li, Xin. "A simulation evaluation of backward elimination and stepwise variable selection in regression analysis." Kansas State University, 2012. http://hdl.handle.net/2097/14094.
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Master of ScienceDepartment of Statistics
Paul Nelson
A first step in model building in regression analysis often consists of selecting a parsimonious set of independent variables from a pool of candidate independent variables. This report uses simulation to study and compare the performance of two widely used sequential, variable selection algorithms, stepwise and backward elimination. A score is developed to assess the ability of any variable selection method to terminate with the correct model. It is found that backward elimination performs slightly better than stepwise, increasing sample size leads to a relatively small improvement in both methods and that the magnitude of the variance of the error term is the major factor determining the performance of both.
5
Daghighi, Amin. "Harmful Algae Bloom Prediction Model for Western Lake Erie Using Stepwise Multiple Regression and Genetic Programming." Cleveland State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=csu1502190026473106.
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6
Maxwell, Kori Lloyd Hugh. "Logistic Regression Analysis to Determine the Significant Factors Associated with Substance Abuse in School-Aged Children." Digital Archive @ GSU, 2009. http://digitalarchive.gsu.edu/math_theses/67.
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Substance abuse is the overindulgence in and dependence on a drug or chemical leading to detrimental effects on the individual’s health and the welfare of those surrounding him or her. Logistic regression analysis is an important tool used in the analysis of the relationship between various explanatory variables and nominal response variables. The objective of this study is to use this statistical method to determine the factors which are considered to be significant contributors to the use or abuse of substances in school-aged children and also determine what measures can be implemented to minimize their effect. The logistic regression model was used to build models for the three main types of substances used in this study; Tobacco, Alcohol and Drugs and this facilitated the identification of the significant factors which seem to influence their use in children.
7
Hu, Qing. "Predictor Selection in Linear Regression: L1 regularization of a subset of parameters and Comparison of L1 regularization and stepwise selection." Link to electronic thesis, 2007. http://www.wpi.edu/Pubs/ETD/Available/etd-051107-154052/.
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SINGH, KEVIN. "Comparing Variable Selection Algorithms On Logistic Regression – A Simulation." Thesis, Uppsala universitet, Statistiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-446090.
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When we try to understand why some schools perform worse than others, if Covid-19 has struck harder on some demographics or whether income correlates with increased happiness, we may turn to regression to better understand how these variables are correlated. To capture the true relationship between variables we may use variable selection methods in order to ensure that the variables which have an actual effect have been included in the model. Choosing the right model for variable selection is vital. Without it there is a risk of including variables which have little to do with the dependent variable or excluding variables that are important. Failing to capture the true effects would paint a picture disconnected from reality and it would also give a false impression of what reality really looks like. To mitigate this risk a simulation study has been conducted to find out what variable selection algorithms to apply in order to make more accurate inference. The different algorithms being tested are stepwise regression, backward elimination and lasso regression. Lasso performed worst when applied to a small sample but performed best when applied to larger samples. Backward elimination and stepwise regression had very similar results.
9
Dawson, Amanda Caroline St Vincent???s Hospital Clinical School UNSW. "Evaluation of novel molecular markers from the WNT pathway : a stepwise regression model for pancreatic cancer survival." Awarded by:University of New South Wales. St Vincent???s Hospital Clinical School, 2007. http://handle.unsw.edu.au/1959.4/31528.
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Optimisation of the conventional tripartite of pancreatic cancer (PC) treatment have led to significant improvements in mortality, however further knowledge of the underlying molecular processes is still required. Transcript profiling of mRNA expression of over 44K genes with microarray technology demonstrated upregulation of secreted frizzled related protein 4 (sFRP4) and ??-catenin in PC compared to normal pancreata. Their pathway ??? Wnt signalling is integral to transcriptional regulation and aberrations in these molecules are critical in the development of many human malignancies. Immunohistochemistry protocols were evaluated by two independent blinded examiners for antigen expression differences associated with survival patterns in 140 patients with biopsy verified PC and a subset of 23 normal pancreata with substantial observer agreement (kappa value 0.6-0.8). A retrospective cohort was identified from 6 Sydney hospitals between 1972-2003 and archival formalin fixed tissue was collected together with clinicopathological data. Three manual stepwise regression models were fitted for overall, disease-specific and relapse-free survival to determine the value of significant prognostic variables in risk stratification. The models were fitted in a logical order using a careful strategy with step by step interpretation of the results. Immunohistochemistry demonstrated increased sFRP4 membranous expression (> 10%) in 49/95 PC specimens and this correlated with improved overall survival (HR:0.99;95%CI:0.97-6.40;LRchi2=134.75; 1df; ??< 0.001). Increased sFRP4 cytoplasmic staining (> 2/3) in 46/85 patients increased the disease-specific survival (HR:0.52;95%CI:0.31-0.89;LR test statistic =248.40;1df;??< 0.001). Increasing ??-catenin membranous expression (< _60%) in 26/116 patients was associated with an increased risk of overall death (HR:3.18;95%CI:1.14-8.89;LR test statistic =4.61;1df,??< 0.05). Increasing cytoplasmic expression in 65/114 patients was protective and was associated with prolonged survival on univariate, but not multivariate analysis (Disease specific survival HR:0.75;95%CI:0.56-1.00;logrank chi2=3.91;1df; ??=0.05). Increased nuclear ??-catenin expression in 65/114 patients was associated with prolonged survival (disease-specific HR:0.92;95%CI:0.83-1.02; LR test statistic= 49.72;1df;??< 0.001). At the conclusion, 12 patients (8.6%) remained alive, 122 died of their disease (68 males versus 54 females). They were followed for a median of 8.7 months (range 1.0-131.3) months. The median age was 66.5 years (range 34.4-96.0, standard deviation 10.9) years. Pancreatic resection was achieved in 79 patients with 46.8% achieving RO resection. The 30 day post-operative mortality was 2.1%. The overall 1 year survival rate was (33.7% ; 95%CI: 25.78-33.79) with a 5 year survival of (2.87%, 95%CI: 2.83-6.01) and a median survival of (8.90 months; 95%CI: 7.5-10.2). The median disease-specific survival was (9.40; 95%CI: 7.9-10.5 months) and the median time to relapse was 1.2 months (95%CI 1.0-1.2 months). A central tenet of contemporary cancer research is that an understanding of the genetic and molecular abnormalities that accompany the development and progression of cancer is critical to further advances in diagnosis, treatment and eventual prevention. High throughput tissue microarrays were used to study expression of two novel tumour markers in a cohort of pancreatic cancer patients and identified sFRP4 and ??-catenin as potential novel prognostic markers.
10
Hinds, H. A. "The application of a modified stepwise regression (MSR) method to the estimation of aircraft stability and control derivatives." Thesis, Cranfield University, 1996. http://hdl.handle.net/1826/3624.
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A programme of research has now been completed in the College of
Aeronautics (CoA) at Cranfield University to investigate the use of a
Modified Stepwise Regression (MSR) procedure. The technique was
applied to data obtained from a small BAe Hawk aircraft model flown in
a dynamic wind tunnel facility in order to try to estimate the
aerodynamic stability and control derivatives of the model.
A variety of preliminary experiments were performed to enable the
static stability of the Hawk model to be evaluated and estimates for a
limited number of aerodynamic derivatives were obtained. The initial
experiments also allowed data acquisition and processing systems to be
developed. Experience of flying and controlling the model in the wind
tunnel was gained.
The MSR technique was implemented in the form of a FORTRAN 77
software program. Computer simulations of both the full scale Hawk
aircraft and scaled wind tunnel model were written. MSR was found to
produce perfect derivative estimates when using noise-free data
produced by the aircraft simulations.
Various mathematical models were produced to represent the reduced
order small perturbation equations of motion for the Hawk in the wind
tunnel. Different methods for re-constructing the perturbation
variables were implemented. Although the MSR procedure did not perform
optimally with experimental data, some insight into both the MSR method
and the practical difficulties associated with using a small dynamic
rig has been gained.
11
Barboza, Fabrício da Silva. "FUNÇÕES DE PEDOTRANSFERÊNCIA PARA SOLOS DO SUL DO URUGUAI." Universidade Federal de Santa Maria, 2011. http://repositorio.ufsm.br/handle/1/7537.
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Conselho Nacional de Desenvolvimento Científico e TecnológicoThe continuous search for information that will assist agricultural practices is today relevant, being the primary use of methodologies to facilitate the determination of relevant parameters in the agricultural productivity. Alternative methods for determining the physical and hydro soils can auxiliary in the monitoring of agricultural activity. Among these, the use stands of pedotransfer functions (FPTs), among other properties, provide an indirect measure of water retention of soil, reducing cost, time and manpower. This study aims to use multiple linear regression models to determine the FPTs for the soils of southern Uruguay to the practical use at laboratories in soil physics, to obtain the curve of retention. For the realization of the work, used 251 samples of superficial, intermediate and inferior soils of southern Uruguay, available in the database of physical analysis of the INIA (Instituto Nacional de Investigación Agropecuaria). This database consists of information of soil texture (percentage sand, silt and clay), bulk density, porosity of the soil, besides the information of water content at potentials of 0, -3, -30, -100, -500 and -1500 kPa. The organization of the database was organized randomly, which is subdivided into two banks, one with 60% of the data (development of FPTs) and the other with 40% of the data (validation of FPTs). The data used to develop the FPTs were included in the Statistical Analysis System (SAS), in its method of determining equations of multiple linear regression (stepwise). Being generated FPTs to estimate water retention at potentials of -30, -100, -500 and -1500 kPa for the superficial layers (0-20 cm), intermediate (20-40 cm) and bottom (40-60 cm ) of the soil profile. The equations presented in its constitution datas textural and structural soil and observed that the statistical indicators mean error and root mean square error squared values were near zero, indicating good accuracy in the determination of residual moisture through the FPTs. In general can say that the attribute structure, water content remaining in the soil after application potential of -3 kPa, was significant in all the FPTs developed. We conclude that the FPTs developed to estimate the water content remaining in the soil at potentials of -30, - 100, -500 and -1500 kPa were good, could be used as an alternative in the construction of water retention curve in soils that have characteristics that fall under the requirements of the FPTs developed for the soils of southern Uruguay.
A busca contínua por informações que venham a auxiliar nas práticas agrícolas é fato relevante nos dias atuais, sendo primordial a utilização de metodologias que facilitem a determinação de parâmetros determinantes na produtividade agrícola, primando pela facilidade e agilidade nas determinações. Métodos alternativos para determinação das características físicohidricas dos solos podem auxiliar no monitoramento da atividade agrícola. Dentre estes, salienta-se o uso de funções de pedotransferência (FPTs) que, entre outras propriedades, possibilitam a determinação indireta da curva de retenção de água do solo, reduzindo custos, tempo e mão-de-obra. O presente estudo objetiva utilizar de modelos de regressão linear múltipla para determinação de FPTs para os solos do Sul do Uruguai, visando a utilização prática destas em laboratórios de física do solo, para a obtenção da curva de retenção dos mesmos. Para a realização do trabalho foram utilizadas 251 amostras das camadas superficial, intermediária e inferior de solos do Sul do Uruguai, disponíveis no banco de dados de análises físicas do INIA (Instituto Nacional de Investigación Agropecuaria). Esse banco de dados é composto por informações de textura do solo (percentuais de areia, silte e argila), densidade do solo, porosidade total do solo, além das informações do conteúdo de água nos potenciais de 0, -3, -30, -100, -500 e -1500 kPa. A organização do banco de dados foi realizada de forma aleatória, sendo este subdividindo em dois bancos, um com 60% dos dados (desenvolvimento das FPTs) e o outro com 40% dos dados (validação das FPTs). Os dados utilizados para o desenvolvimento das FPTs foram inseridos no programa Statistical Analysis System (SAS), em seu método de determinação de equações de regressão linear múltipla (Stepwise). Sendo geradas FPTs para estimar a retenção de água nos potenciais de -30, -100, - 500 e -1500 kPa, para as camadas superficial (0-20 cm), intermediária (20-40 cm) e inferior (40-60 cm) do perfil do solo. As equações obtidas apresentaram em sua constituição atributos texturais e estruturais do solo, sendo observado que, os indicadores estatísticos erro médio e raiz quadrada do erro médio ao quadrado apresentaram valores próximos a zero, indicando boa acurácia na determinação da umidade residual através das FPTs estimadas. De modo geral pode-se afirmar que, o atributo estrutural, conteúdo de água remanescente no solo após aplicação de potencial de -3 kPa, foi significativo em todas as FPTs desenvolvidas. Conclui-se que as FPTs desenvolvidas para estimar o conteúdo de água remanescente no solo nos potenciais de -30, -100, -500 e -1500 kPa apresentam-se satisfatórias, podendo ser utilizadas como alternativa na construção da curva de retenção de água em solos que apresentem características que o enquadrem nos requisitos das FPTs desenvolvidas para os solos do Sul do Uruguai.
12
Alm, Micael. "Probability Modelling of Alpine Permafrost Distribution in Tarfala Valley, Sweden." Thesis, Uppsala universitet, Luft-, vatten och landskapslära, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-323971.
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Datainsamling har genomförts i Tarfaladalen under 5 dagar vid månadsskiftet mellan mars och april 2017. Insamlingen resulterade i 36 BTS-mätningar (Bottom Temperature of Snow cover) som därefter har använts tillsammans med data från tidigare insamlingar, till att skapa en sammanställd modell över förekomsten av permafrost omkring Tarfala. En statistisk undersökning syftade till att identifiera meningsfulla parametrar som permafrost beror av, genom att testa de oberoende variablerna mot BTS i en stegvis regression. De oberoende faktorerna höjd över havet, aspekt, solinstrålning, vinkel och gradient hos sluttningar producerades för varje undersökt BTS-punkt i ett geografiskt informationssystem. Den stegvisa regressionen valde enbart höjden som signifikant variabel, höjden användes i en logistisk regression för att modellera permafrostens utbredning. Den slutliga modellen visade att permafrostens sannolikhet ökar med höjden. För att skilja mellan kontinuerlig, diskontinuerlig och sporadisk permafrost delades modellen in i tre zoner med olika sannolikhetsspann. Den kontinuerliga permafrosten är högst belägen och därav den zon där sannolikheten för permafrost är störst, denna zon gränsar till den diskontinuerliga permafrosten vid en höjd på 1523 m. Den diskontinuerliga permafrosten har en sannolikhet mellan 50–80 % och dess undre gräns på 1108 m.ö.h. separerar den diskontinuerliga zonen från den sporadiska permafrostenA field data collection has been carried out in Tarfala valley at the turn of March to April 2017. The collection resulted in 36 BTS-measurements (Bottom Temperature of Snow cover) that has been used in combination with data from earlier surveys, to create a model of the occurrence of permafrost around Tarfala. To identify meaningful parameters that permafrost relies on, independent variables were tested against BTS in a stepwise regression. The independent variables elevation, aspect, solar radiation, slope angle and curvature were produced for each investigated BTS-point in a geographic information system. The stepwise regression selected elevation as the only significant variable, elevation was applied to a logistic regression to model the permafrost occurrence. The final model showed that the probability of permafrost increases with height. To distinguish between continuous, discontinuous and sporadic permafrost, the model was divided into three zones with intervals of probability. The continuous permafrost is the highest located zone and therefore has the highest likelihood, this zone delimits the discontinuous permafrost at 1523 m a.s.l. The discontinuous permafrost has probabilities between 50-80 % and its lower limit at 1108 m a.s.l. separates the discontinuous zone from the sporadic permafrost.
13
Carlos, Mark E. "An Analysis of Wind Power Plant Site Prospecting in the Central United States." OpenSIUC, 2010. https://opensiuc.lib.siu.edu/dissertations/215.
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Rapid deployment of terrestrial wind power plants (WPPs) is a function of accurate identification of areas suitable for WPPs. Efficient WPP site prospecting not only decreases installation lead time, but also reduces site selection expenses and provides faster reductions of greenhouse gas emissions. Combining conventional predictor variables, such as wind strength and proximity to transmission lines, with nonconventional socioeconomic and demographic predictor variables, will result in improved identification of suitable counties for WPPs and therefore accelerate the site prospecting phase of wind power plant deployment. Existing and under-construction American terrestrial WPPs located in the top 12 windiest states (230 as of June 2009) plus 178 potential county level predictor variables are introduced to logistic regression with stepwise selection and a random sampling validation methodology to identify influential predictor variables. In addition to the wind resource and proximity to electricity transmission lines, existence of a Renewable Portfolio Standard, the population density within a 200 mile radius of the county center, median home values, and farm land area in the county are the four strongest nonconventional predictors (Hosmer and Lemeshow Chi-Square = 9.1250, N = 1009, df = 8, p = 0.3319, - 2LogLikelihood = 619.521). Evaluation of the final model using multiple statistics, including the Heidke skill score (0.2647), confirms overall model predictive skill. The model identifies the existence of 238 suitable counties in the twelve state region that do not possess WPPs (~73% validated overall accuracy) and eliminates 654 counties that are not classified as suitable for WPPs. The 238 counties identified by the model represent ideal counties for further exploration of WPP development and possible transmission line construction. The results of this study will therefore allow faster integration of renewable energy sources and limit climate change impacts from increasing atmospheric greenhouse gas concentrations.
14
Elving, Hannes. "Kvicksilversituationen i Stockholms skärgård." Thesis, Uppsala University, LUVAL, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-113328.
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Kvicksilverutsläppen har på senare år minskat i omfattning men utsläpp sker fortfarande och det finns ett stort lager i naturen. Oorganiskt kvicksilver är relativt ofarligt för levande organismer, men i akvatiska miljöer kan sulfatreducerande bakterier under syrefria förhållanden omvandla oorganiskt kvicksilver till den betydligt mer skadliga formen metylkvicksilver, meHg, som även är mer biotillgängligt än oorganiskt kvicksilver. Kvicksilver biomagnifieras uppåt i trofinivåerna, från att vara lägst halter i plankton och bottenfauna till att vara högst halter i rovfiskar. Kvicksilver ackumuleras även i fiskars muskelvävnad vilket innebär att yngre fiskar har lägre Hg-halter än gamla och stora individer. På grund av detta finns kostråd framtagna av Livsmedelsverket. Saluförd abborre, liksom ett flertal andra fiskarter, får inneha maximalt 0,5 mg Hg/kg fiskmuskel (färskvikt) och för gädda är gränsen satt till 1 mg Hg/kg fiskmuskel (färskvikt). Organiskt kvicksilver kan påverka foster negativt, och därför bör kvinnor i fertil ålder i största möjliga mån undvika kvicksilverrik fisk.
Examensarbetet syftar till att belysa kvicksilversituationen i Stockholms skärgård för stationär kustfisk. Information har samlats in dels genom en litteraturstudie och dels genom fältundersökningar utförda av IVL Svenska Miljöinstitutet. Genom statistisk analys och stegvis multipel regression visades att kvicksilverhalten i sediment, vattnets klorofyllhalt och områdets vattenvolym bidrog med förklaringsgrad till halten Hg i fisk. Utifrån de mest signifikanta förklarande variablerna togs en statistisk modell fram i syfte att kunna prediktera teoretiska kvicksilverhalter i fisk. Olika modellkombinationer testades och utgående från en modellvalidering valdes den bästa modellen ut. Dess förklaringsgrad är 81 % där kvicksilverhalten i sediment är modellens enda variabel.
Kvicksilversituationen i Stockholms skärgårds kustområden visades grafiskt med hjälp av interpolerade GIS-kartor. Samma områdesavgränsningar användes som i SMHI:s havsområderegister. Det visades att situationen över lag är relativt god, med undantag för de centrala delarna av Stockholm och på så vis kan Stockholm ses som en förorenande punktkälla.
Mercury emissions have been reduced in recent years but the discharges still exist and there exist a great mercury stock out in the nature. Inorganic mercury is relatively harmless for living organisms but during shortage of oxygen, sulphur reducing bacteria can transform inorganic mercury into the considerable more toxic substance methyl mercury, meHg, that are more bio available than inorganic mercury. Mercury biomagnify upwards the trophic levels, where the lowest content exists in algae and sediment living fauna and the highest content exist in predator fishes. Mercury also accumulates in fishes muscle tissue, meaning that young fishes have lower mercury content than old and big individuals. Food advices from the Swedish food agency exist because of this. Perch offered for sale are allowed to have a content of maximum 0.5 mg Hg/kg fish muscle (wet weight) and for pike the upper boundary content is 1 mg Hg/kg fish muscle (wet weight). Inorganic mercury can affect foetus negatively, and therefore women in fertile age should avoid fish with high mercury content for as long as possible.
The aim of this exam work is to illustrate the mercury situation in the archipelago of Stockholm regarding stationary coast fish. Information was collected through a literature study and by field examines done by IVL Swedish Environmental Research Institute Ltd. Through statistical analyses and stepwise multiple regression it was shown that the mercury content in sediment, chlorophyll and the water volume of the area contributed by statistical explanation to the mercury concentration in fish. On the basis of the most significant variables a statistical model was created, with the purpose of predicting theoretical mercury contents in fish. Different model combinations were tested and by a model validation the best model were chosen. Its statistical explanation is 81 % were the mercury content in the sediment is the only input variable to the model.
The mercury situation in the Stockholm archipelago was presented graphically by interpolated maps created with GIS. The same area boundary as SMHI’s maritime registry was used. It was shown that the situation in general is relatively good, with the exception of the central parts of Stockholm. Because of this Stockholm can be seen as a polluting point source.
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Sahin, Mehmet Altug. "Regional Flood Frequency Analysis For Ceyhan Basin." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615439/index.pdf.
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Regional flood frequency techniques are commonly used to estimate flood quantiles when flood data are unavailable or the record length at an individual gauging station is insufficient for reliable analyses. These methods compensate for limited or unavailable data by pooling data from nearby gauged sites. This requires the delineation of hydrologically homogeneous regions in which the flood regime is sufficiently similar to allow the spatial transfer of information. Therefore, several Regional Flood Frequency Analysis (RFFA) methods are applied to the Ceyhan Basin. Dalyrmple (1960) Method is applied as a common RFFA method used in Turkey. Multivariate statistical techniques which are Stepwise and Nonlinear Regression Analysis are also applied to flood statistics and basin characteristics for gauging stations. Rainfall, Perimeter, Length of Main River, Circularity, Relative Relief, Basin Relief, Hmax, Hmin, Hmean and H&Deltaare the simple additional basin characteristics. Moreover, before the analysis started, stations are clustered according to their basin characteristics by using the combination of Ward&rsquo
s and k-means clustering techniques. At the end of the study, the results are compared considering the Root Mean Squared Errors, Nash-Sutcliffe Efficiency Index and % difference of results. Using additional basin characteristics and making an analysis with multivariate statistical techniques have positive effect for getting accurate results compared to Dalyrmple (1960) Method in Ceyhan Basin. Clustered region data give more accurate results than non-clustered region data. Comparison between clustered region and non-clustered region Q100/Q2.33 reduced variate values for whole region is 3.53, for cluster-2 it is 3.43 and for cluster-3 it is 3.65. This show that clustering has positive effect in the results. Nonlinear Regression Analysis with three clusters give less errors which are 29.54 RMSE and 0.735 Nash-Sutcliffe Index, when compared to other methods in Ceyhan Basin.
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Conte, Bianchecci Danielli. "Predição do peso e do rendimento de filé de tilápia do nilo a partir de medidas ultrassonográficas e morfométricas, e validação dos modelos de regressão." Universidade Estadual do Oeste do Paraná, 2011. http://tede.unioeste.br:8080/tede/handle/tede/1639.
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This study aimed to predict the fillet weight (PF) and fillet yield (RF) of Nile tilapia (Oreochromis niloticus) from external measures, measured by morphometry and measures of epiaxial muscles using ultrasound and validate the estimated equations using another sample biometric data. A total of 102 adult fish GIFT lineage, reversed males weighing between 260 and 580 g had the total weight (PT) and body circumference average (CR) all measured by ultrasonography in four predefined body regions (1) between the basis of anterior (2) between the basis of anteriour insertion of anal fin to the last hard ray of dorsal fin. (3) between the final insertion of anal and dorsal fins and (4) between the ventral and dorsal insertion of caudal fin. The prediction equations from the measurements performed on 50 samples were analyzed by statistical procedures backward and stepwise. The measurements made in remaining 52 samples were used for validation of predictive equations to PF and RF. The validation were made from adjustment of linear models first degree of values observed above the values predict on each regression equation set. The equations PFx and RFx estimated from data collected of ultrasound images showed coefficient of determination (R2) of 0.53 (PF1 = -17.35 + 3.66HD2 45.20LE4 + 0.55AE2 + 4.64AE4) e 0.15 (RF1 = 26.66 + 0.043AE2), in backward, and 0.53 (PF2 = -58.03 + 5.65HE4 + 0.33AD1 + 0.65AD2) e 0.19 (RF2 = 25.02 + 0.051AD2), in stepwise. The inclusion of measures of CR and PT as regressive equations did allow the equations to show higher values of R2 such as 0.97 (PF3= - 52.25 1.26HE1 2.03HE3 + 0.40PT +0.51CR e PF4 = -18.12 1.20HE1 + 0.425PT) and 0.73 (RF3 = 17.83 0.29HE1 0.49HE3 + 0.02PT + 0.13CR), in backward and stepwise, and 0.68 (RF4 = 26,14 - 0,27HE1 + 0,027PT), in stepwise, and lower values of mean square of residue that these regression models presented high adherence to data of PF and RF. About the validation of prediction equations all of it were effective in estimating the PF and RF in the sample evaluated. The equations (P = 1.0000) PF3, PF4 (P = 0.5401), RF3 (P = 1.0000) and RF4 (P = 0.8363) were the most accurate and applicable in predicting PF and RF in Nile tilapia. The height of the left side body regions 1 and 3, measured by ultrasound images, together with the average body weight and circumference, are important in predicting of regressive of PF and RF of Nile tilapia. The regression equations, PF3, PF4, RF3, and RF4 are recommended for estimating the PF and RF of Tilapia in phenotypic males adult Nile tilapia GIFT lineage, weighing between 260 and 580 g
Este estudo teve por objetivos predizer o peso de filé (PF) e o rendimento de filé (RF) de tilápia do Nilo (Oreochromis niloticus), a partir de medidas externas mensuradas por morfometria e medidas da musculatura epiaxial, mensuradas por ultrassonografia, e validar as equações estimadas utilizando outra amostra de dados biométricos. Um total de 102 peixes adultos, da linhagem GIFT, machos invertidos, pesando entre 260 e 580 g, foram avaliados quanto ao peso total (PT), circunferência corporal média (CR) e mensurados por ultrassonografia em quatro regiões corpóreas pré-definidas: (1) entre a base de inserção anterior da nadadeira pélvica até o término anterior da nadadeira dorsal, (2) entre a base da inserção anterior da nadadeira anal até o último raio duro da nadadeira dorsal, (3) entre a inserção final das nadadeiras anal e dorsal e (4) entre a inserção ventral e dorsal da nadadeira caudal. As equações de predição a partir das mensurações realizadas em 50 exemplares foram analisadas pelos procedimentos estatísticos backward e stepwise. As mensurações feitas nos 52 exemplares restantes foram utilizadas para a validação das equações preditoras para PF e RF. A validação foi feita a partir do ajuste de modelos lineares de 1° grau dos valores observados sobre os valores preditos por cada equação de regressão definida. As equações PFx e RFx, estimadas em função dos dados coletados das imagens ultrassonográficas, apresentaram valores de coeficiente de determinação (R²) de 0,53 (PF1 = -17,35 + 3,66HD2 - 45,20LE4 + 0,55AE2 + 4,64AE4) e 0,15 (RF1 = 26,66 + 0,043AE2), no backward, e 0,53 (PF2 = -58,03 + 5,65HE4 + 0,33AD1 + 0,65AD2) e 0,19 (RF2 = 25,02 + 0,051AD2), no stepwise. A inclusão das medidas de CR e PT como regressoras permitiu que as equações apresentassem R² mais elevados, com valores de 0,97 (PF3 = - 52,25 - 1,26HE1 - 2,03HE3 + 0,40PT +0,51CR e PF4 = -18,12 - 1,20HE1 + 0,425PT) e 0,73 (RF3 = 17,83 - 0,29HE1 - 0,49HE3 + 0,02PT + 0,13CR), no backward e no stepwise, e 0,68 (RF4 = 26,14 - 0,27HE1 + 0,027PT), no stepwise, e menores valores de quadrado médio do resíduo, indicando que esses modelos de regressão apresentaram elevada aderência aos dados de PF e RF. Na validação das equações preditoras, todas foram eficientes em estimar o PF e o RF na amostra avaliada. As equações PF3 (P = 1,0000), PF4 (P = 0,5401), RF3 (P = 1,0000) e RF4 (P = 0,8363) foram as mais precisas e aplicáveis na predição de PF e RF em tilápia do Nilo. A altura do lado esquerdo nas regiões corporais 1 e 3, mensuradas por imagens ultrassonográficas, em conjunto com o peso e a circunferência corporal média, são regressoras importantes na predição do PF e RF de tilápia do Nilo. As equações de regressão PF3, PF4, RF3 e RF4 são recomendadas para estimar o PF e o RF de tilápia no Nilo adultas, machos fenotípicos, linhagem GIFT, com peso entre 260 e 580g
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Salam, Md. "Time and cost overruns on high-rise building construction in Bangladesh." Thesis, Abertay University, 2007. https://rke.abertay.ac.uk/en/studentTheses/15bbc393-0b06-4691-a6ec-1e6a6d925179.
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Construction projects in developing countries may suffer from time overruns, which are associated with cost overruns. This research project investigated both time and cost overruns on high-rise building projects in Dhaka, Bangladesh. Surprisingly, preliminary data analysis showed negligible cost overruns in comparison to time overruns. So, further analysis o f cost overruns was not considered in this thesis. This research project also investigated how the causes o f time-overruns can be mitigated. 72 time-overrun and 22 cost-overrun variables were identified through a literature review. These variables were taken as parameters and a personal interview survey was conducted with developers, consultants, contractors and project managers using semistructured questionnaire. A similar second survey was conducted using 22 measures, which can mitigate time- overruns. Data analysis involved the relative importance index to rank the variables, factors analysis to reduce variables to factors with minimum loss of data, stepwise regression to find links among factors in successive stages of construction process and multiple regression to explain delays in terms of factors. The main causes o f time-overruns were ‘cash flow’, ‘planning and scheduling deficiency’ and ‘design changes’. A scree graph identified 31 important variables that caused delays but factor analysis reduced these to 14 factors. Stepwise regression found no strong links among the factors to identify them as reasons for delay in successive stages of the construction project. A multiple regression model explained about 85% of the variance of the delays using eight factors. The main individual measures mitigating time-overruns were ‘improvement of cash flow’, ‘improvement o f communication and coordination among project participants’ and ‘development o f robust planning and scheduling instruments’. Factor analysis produced ten representative factors. Stepwise regression could not find strong links among factors mitigating time-overruns in successive stages of the construction project.
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Doan, Alisa Rebekah. "Determining a sensory model for predicting successful and unsuccessful products: a case study of flavors for a snack category." Diss., Kansas State University, 2010. http://hdl.handle.net/2097/4329.
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Doctor of PhilosophyDepartment of Human Nutrition
Edgar Chambers IV
Companies introduce new products with the goal of achieving success. However, many products fail. The overall objective of this research was to design processes for determining sensory and market characteristics of food products that could predict success. The first sub-objective was to determine if success could be predicted using information known before launch. The second sub-objective was to describe a process for determining specific sensory characteristics that promote success. Most methods chosen for this research are commonly used. However, previous research has identified a relationship between consumers liking and salivation, without defining a method. Thus, three salivation methods were selected for initial testing: spit, cotton rolls and sensory scale. These were tested on foods with different textures. Although all methods gave similar results, the spit method was chosen for further testing of flavor differences. Differences in salivation measurements were found for snacks where flavors were different but texture was unchanged. Next, flavored snack products from 15 countries were selected that were successful or had failed. Questionnaires were completed for each product and included questions related to authenticity, familiarity, current trends, packaging and marketplace issues such as product competition and pricing, all of which would be known before launch. A discriminant function was developed that correctly identified 75.8% of the successful flavored snack products as successful and 66.7% of the unsuccessful products as unsuccessful. Stepwise comparisons were used to determine that four variables are necessary to correctly categorize these products. The products then were clustered into three groups to select 34 products from 11 countries for further sensory testing. Information from extensive sensory descriptive methods were evaluated individually and in various combinations through stepwise regression and discriminant analysis. The final sensory model correctly predicted all successful and unsuccessful products, had an R-square of 0.84 and included nine regression factors: seven flavor attributes and two flavor attribute ratios. Many of the attributes were base flavor notes necessary for this flavored snack category. A process for selecting key attributes for success was described. For this snack category, creating products with flavors that interact well with base flavor notes can lead to a successful product.
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Zhu, Di. "Analysis of Factors Affecting Motorcycle-Motor Vehicle Crash Characteristics." University of Dayton / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1406031500.
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Grego, Simone. "Modelos para relacionar variáveis de solos e área basal de espécies florestais em uma área de vegetação natural." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-03122014-142123/.
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O padrão espacial de ocorrência de atributos de espécies florestais, tal como a área basal das árvores, pode fornecer informações para o entendimento da estrutura da comunidade vegetal. Uma vez que fatores ambientais podem influenciar tanto o padrão espacial de ocorrência quanto os atributos das espécies em florestas nativas. Desse modo, investigar a relação entre as características ambientais e o padrão espacial de espécies florestais pode ajudar a entender a dinâmica das florestas. Especificamente, neste trabalho, o objetivo é avaliar métodos estatísticos que permitam identificar quais atributos do solo são capazes de explicar a variação da área basal de cada espécie de árvore. A área basal foi considerada como variável resposta e como covariáveis, um grande número de atributos físicos e químicos do solo, medidos em uma malha de localizações cobrindo a área de estudo. Foram revisados e utilizados os métodos de regressão linear múltipla com método de seleção stepwise, modelos aditivos generalizados e árvores de regressão. Em uma segunda fase das análises, adicionou-se um efeito espacial aos modelos, com o intuito de verificar se havia ainda padrões na variabilidade, não capturados pelos modelos. Com isso, foram considerados os modelos autoregressivo simultâneo, condicional autoregressivo e geoestatístico. Dado o grande número de atributos do solo, as análises foram também conduzidas utilizando-se as covariáveis originais, fatores identificados em uma análise fatorial prévia dos atributos de solo. A seleção de modelos com melhor ajuste foi utilizada para identificar os atributos de solo relevantes, bem como a presença e melhor descrição de padrões espaciais. A área de estudo foi a Estação Ecológica de Assis, da Unidade de Conservação do Estado de São Paulo em parcelas permanentes, dentro do projeto \"Diversidade, Dinâmica e Conservação em Florestas do Estado de São Paulo: 40 ha de parcelas permanentes\", do programa Biota da FAPESP. As análises reportadas aqui se referem à área basal das espécies Copaifera langsdorffii, Vochysia tucanorum e Xylopia aromatica. Com os atributos de solo reduzidos e consistentemente associados à área basal, a declividade, altitude, saturação por alumínio e potássio mostraram-se relevantes para duas das espécies. Resultados obtidos mostraram a presença de um padrão na variabilidade, mesmo levando-se em consideração os efeitos das covariáveis, ou seja, os atributos do solo explicam parcialmente a variabilidade da área basal, mas existe um padrão que ocorre no espaço que não é capturado por essas covariáveis.The spatial pattern of occurrenceis of forest species and their attributes, such as the basal area of trees, can provide information for understanding the structure of the vegetable community. Considering the environmental factors can influence the spatial pattern of occurrences of species in native forests and related attributes, describing relationship between environmental characteristics and spatial pattern of forest species can be associated with the dynamics of forests. The objective of the present study is to assess different statistical methods used to identify which soil attributes are associated with the basal area of each tree selected species. The basal area was considered as the response variable and the covariates are given by a large number of physical and chemical attributes of the soil, measured at a grid of locations covering the study area. The methods considered are the multiple linear regression with stepwise model selection, generalized additive models and regression trees. Spatial effects were added to the models, in order to ascertain whether there is residual spatial patterns not captured by the covariates. Thus, simultaneous autoregressive model, autoregressive conditional and geostatistical were considered. Considering the large number of soil attributes, analysis were were conducted both ways, using the original covariates, and using factors identified in a preliminar factor analysis of the soil attributes. Model selection was used to identify the relevant attributes of soil as well as the presence and better description of spatial patterns. The study area was the Ecological Station of Assis, the Conservation Unit of the State of São Paulo in permanent plots within the \"Diversity Dynamics and Conservation Forests in the State of São Paulo: 40 ha of permanent plots\" project, under the research project FAPESP biota. The analyzes reported here refer to the basal area of the species Copaifera langsdorffii, Vochysia tucanorum and Xylopia aromatica. Results differ among the considered methods reinforcing the reccomendation of considering differing modeling strategies. Covariates consistently associated with basal area are slope, altitude and aluminum saturation, potassium, relevant to at least two of the species. Results obtained showed the presence of patterns in residual variability, even taking into account the effects of covariates. The soil characteristics only partially explain the variability of the basal area and there are spatial patterns not captured by these covariates.
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Shorter, Nichole. "COMPARING ASSESSMENT METHODS AS PREDICTORS OF STUDENT LEARNING IN UNDERGRADUATE MATHEMATICS." Master's thesis, University of Central Florida, 2008. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2729.
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This experiment was designed to determine which assessment method: continuous assessment (in the form of daily in-class quizzes), cumulative assessment (in the form of online homework), or project-based learning, best predicts student learning (dependent upon posttest grades) in an undergraduate mathematics course. Participants included 117 university-level undergraduate freshmen enrolled in a course titled "Mathematics for Calculus". Initially, a multiple regression model was formulated to model the relationship between the predictor variables (the continuous assessment, cumulative assessment, and project scores) versus the outcome variable (the posttest scores). However, due to the possibility of multicollinearity present between the cumulative assessment predictor variable and the continuous assessment predictor variable, a stepwise regression model was implemented and caused the cumulative assessment predictor variable to be forced out of the resulting model, based on the results of statistical significance and hypothesis testing. The finalized stepwise regression model included continuous assessment scores and project scores as predictor variables of students' posttest scores with a 99% confidence level. Results indicated that ultimately the continuous assessment scores best predicted students' posttest scores.M.S.
Department of Mathematics
Sciences
Mathematical Science MS
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Lanzarin, Karina. "RELAÇÕES MORFOMÉTRICAS E POTENCIAL DE MANEJO DE Maclura tinctoria (L.) D. Don Ex. Steud EM FORMAÇÕES SECUNDÁRIAS NO NOROESTE DO RIO GRANDE DO SUL." Universidade Federal de Santa Maria, 2016. http://repositorio.ufsm.br/handle/1/8789.
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Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorThe objective of this study was to characterize Maclura tinctoria individuals in anthropic secondary formations, as their growth aspects in diameter and basal area, their morphometric relationships, spatial distribution and crown regularity. Also analyzing the behavior of individuals with more than one trunk, called multitrunks, and establish regression models to estimate basal area increment, crown diameter and height. For this, they were measured in two distinct areas in Porto Mauá, RS, diameter at breast height, total height, crown diameter and punctual density of each individual (using Bitterlich method). The morphometric indices were calculated based on data obtained from the field. The regularity of the crown was obtained by the coefficient of variation of the crown rays. For spatial analysis was calculated K Ripley function. The annual periodic increment in diameter (IPAd) and basal area (IPAg) were obtained by analysis of growth rings. In order to verify if these variables influence increments, Pearson correlation analysis was performed. It was developed mathematical equations, the stepwise method to estimate the increment in basal area, crown diameter and total height. The tendency of multitrunks individuals in relation to the single-stem for all variables was verified using analysis of covariance. The multitrunks trees in general show a similar tendency to the trees with a single stem. The studied species have moderate growth to fast, presenting therefore great potential for management. The spatial distribution indicated groupings to a higher range to 15 meters. Morphometric indices varied widely, demonstrating the plasticity of the species. As the variation in crown rays was extensive, featuring its irregularity. The morphometric variables, did not exert significant influence on the increment in diameter of Maclura tinctoria individuals. This indicates that the growth in diameter is statistically the same regardless of tree form. However, the degree of slenderness and comprehensiveness index correlated with the periodic increment in basal area. It was possible to define equations with good settings for height, crown diameter and increment in basal area of the species. All the elaborate equations had dbh as dependent variable, indicating the strong correlation of this variable with the other characteristics of trees Maclura tinctoria.
O objetivo do presente trabalho foi caracterizar indivíduos de Maclura tinctoria em formações secundárias antropizadas, quanto a seus aspectos de crescimento em diâmetro e área basal, suas relações morfométricas, distribuição espacial e regularidade da copa. Além de analisar o comportamento de indivíduos com mais de um fuste, denominados multitroncos, e ainda elaborar modelos de regressão para estimar o crescimento em área basal, diâmetro de copa e altura. Para isso, foram medidos, em duas áreas distintas em Porto Mauá, RS, o diâmetro à altura do peito, altura total, diâmetro de copa e densidade pontual (pelo método de Bitterlich) de cada indivíduo. Os índices morfométricos foram calculados com base nos dados obtidos à campo. A regularidade da copa foi obtida através do coeficiente de variação dos raios de copa. Para análise espacial calculou-se a função K de Ripley. O incremento periódico anual em diâmetro (IPAd) e em área basal (IPAg) foram obtidos por análise dos anéis de crescimento. A fim de verificar que variáveis influenciam nestes incrementos, foi realizada análise de correlação de Pearson. Elaborou-se equações matemáticas, pelo método stepwise, para estimar o incremento em área basal, diâmetro de copa e altura total. A tendência dos indivíduos multitroncos em relação aos com fuste único para todas as variáveis foi verificada utilizando análise de covariância. As árvores multitroncos no geral demonstram tendência semelhante às árvores com fuste único. A espécie estudada possui crescimento moderado à rápido, apresentando, portanto, grande potencial para manejo. A distribuição espacial indicou agrupamentos para uma escala superior a 15 metros. Os índices morfométricos variaram amplamente, demonstrando a plasticidade da espécie. Assim como a variação nos raios de copa foi ampla, caracterizando sua irregularidade. As variáveis morfométricas, não exerceram influência significativa no incremento em diâmetro dos indivíduos de Maclura tinctoria. O que indica que o crescimento em diâmetro é estatisticamente o mesmo, independente da forma da árvore. Contudo, o grau de esbeltez e índice de abrangência apresentaram correlação com o incremento periódico em área basal. Foi possível definir equações com bons ajustes para a altura, diâmetro de copa e incremento em área basal da espécie. Todas as equações elaboradas tiveram como variável dependente o DAP, indicando a forte correlação desta variável com as demais características das árvores de Maclura tinctoria.
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Arafat, Md Yasin. "Three Essays on the Evolution of the Determinants of Educational Attainment and its Consequences." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/99465.
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The dissertation focuses on the different determinants of education, their effects on the educational outcome, and the overall effect of education on the lifetime consequences.
The first chapter focuses on the inequality of educational opportunity across different demographic factors. This chapter employs a broader set of social factors to provide fresh insights into the inequality situation in the USA relative to those of the extant literature. The chapter employs polynomial trends for the effects of social factors to identify long-term trends in the determinants of the differences in attainment of each of four achievements (high school graduation, some college, college graduation, and post-college work) across different endogenous social groups. Using the Panel Study of Income Dynamics (PSID) data for the years of 1968-2013, we show how inequality of educational opportunity and its determinants have evolved over the years. The chapter utilizes the machine-learning process and logistic regression model to identify inequality of opportunity.
The second chapter examines the age demographic distribution of graduates across cohorts from 1940 until 1990. Using the PSID data, the paper explored the first and second moment of the age of graduating from high school and college across the US. To deal with the data deficiencies, a large part of the chapter dealt with data preparation. The chapter provides a unique method of extracting information on the graduating age of the individuals both from high school and from college. The results show a large dispersion across the full sample. The data truncated to a standard length, however, provides a much smaller dispersion and much smaller moments. The chapter concludes that as the time passes, people tend to attain education at a younger age.
The third chapter investigates the trends of the contribution of different factors of income starting from 1910 cohort. Following Mincer (1974), a wave of papers studied how various factors contribute to the earnings of individuals. This paper contributes to that literature in three ways: (i) using the PSID data, it computes the actual working experience of the individuals, (ii) it studies the cohorts who were born in 1910 or afterwards, unlike the existing papers, and (iii) it adds two variables�"technological progress and the occupation with which individuals start their careers�"to an extended Mincerian equation. The results re-emphasize the importance of education in lifetime earnings. The results also show that while some of the determinants of income have become more important over the years, other factors have not changed much in importance.PHD
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Wang, Mengchao. "Sensitivity analysis and evolutionary optimization for building design." Thesis, Loughborough University, 2014. https://dspace.lboro.ac.uk/2134/16282.
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In order to achieve global carbon reduction targets, buildings must be designed to be energy efficient. Building performance simulation methods, together with sensitivity analysis and evolutionary optimization methods, can be used to generate design solution and performance information that can be used in identifying energy and cost efficient design solutions. Sensitivity analysis is used to identify the design variables that have the greatest impacts on the design objectives and constraints. Multi-objective evolutionary optimization is used to find a Pareto set of design solutions that optimize the conflicting design objectives while satisfying the design constraints; building design being an inherently multi-objective process. For instance, there is commonly a desire to minimise both the building energy demand and capital cost while maintaining thermal comfort. Sensitivity analysis has previously been coupled with a model-based optimization in order to reduce the computational effort of running a robust optimization and in order to provide an insight into the solution sensitivities in the neighbourhood of each optimum solution. However, there has been little research conducted to explore the extent to which the solutions found from a building design optimization can be used for a global or local sensitivity analysis, or the extent to which the local sensitivities differ from the global sensitivities. It has also been common for the sensitivity analysis to be conducted using continuous variables, whereas building optimization problems are more typically formulated using a mixture of discretized-continuous variables (with physical meaning) and categorical variables (without physical meaning). This thesis investigates three main questions; the form of global sensitivity analysis most appropriate for use with problems having mixed discretised-continuous and categorical variables; the extent to which samples taken from an optimization run can be used in a global sensitivity analysis, the optimization process causing these solutions to be biased; and the extent to which global and local sensitivities are different. The experiments conducted in this research are based on the mid-floor of a commercial office building having 5 zones, and which is located in Birmingham, UK. The optimization and sensitivity analysis problems are formulated with 16 design variables, including orientation, heating and cooling setpoints, window-to-wall ratios, start and stop time, and construction types. The design objectives are the minimisation of both energy demand and capital cost, with solution infeasibility being a function of occupant thermal comfort. It is concluded that a robust global sensitivity analysis can be achieved using stepwise regression with the use of bidirectional elimination, rank transformation of the variables and BIC (Bayesian information criterion). It is concluded that, when the optimization is based on a genetic algorithm, that solutions taken from the start of the optimization process can be reliably used in a global sensitivity analysis, and therefore, there is no need to generate a separate set of random samples for use in the sensitivity analysis. The extent to which the convergence of the variables during the optimization can be used as a proxy for the variable sensitivities has also been investigated. It is concluded that it is not possible to identify the relative importance of variables through the optimization, even though the most important variable exhibited fast and stable convergence. Finally, it is concluded that differences exist in the variable rankings resulting from the global and local sensitivity methods, although the top-ranked solutions from each approach tend to be the same. It also concluded that the sensitivity of the objectives and constraints to all variables is obtainable through a local sensitivity analysis, but that a global sensitivity analysis is only likely to identify the most important variables. The repeatability of these conclusions has been investigated and confirmed by applying the methods to the example design problem with the building being located in four different climates (Birmingham, UK; San Francisco, US; and Chicago, US).
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Conradie, Jessica Kate. "Modelling population dynamics of Leysera gnaphalodes in Namaqualand, South Africa." Diss., Connect to this title online, 2003. http://upetd.up.ac.za/thesis/available/etd-02182004-083915.
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Silva, Marcelo Rubia da [UNESP]. "Modelação e análise da vida útil (metrológica) de medidores tipo indução de energia elétrica ativa." Universidade Estadual Paulista (UNESP), 2010. http://hdl.handle.net/11449/87039.
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O estudo da confiabilidade operacional de equipamentos se tornou fundamental para as empresas possuírem o devido controle dos seus ativos, tanto pelo lado financeiro quanto em questões de segurança. O estudo da taxa de falha de equipamentos prevê quando as falhas irão ocorrer possibilitando estabelecer atitudes preventivas, porém, seu estudo deve ser realizado em condições de operação estabelecidas e fixas. Os medidores de energia elétrica, parte do ativo financeiro das concessionárias de energia, são equipamentos utilizados em diversas condições de operação, tanto nas condições do fluxo de energia, tais como presenças de harmônicos, subtensões, sobre-tensões e padrões de consumo distintos, quanto pelo local físico de instalação, tais como maresia, temperatura, umidade, etc. As falhas nos medidores eletromecânicos de energia elétrica são de difícil constatação uma vez que a maioria dos erros de medição, ocasionados principalmente por envelhecimento de componentes, não alteram a qualidade da energia fornecida e nem interrompem o seu fornecimento. Neste sentido, este trabalho propõe uma nova metodologia de determinação de falhas em medidores eletromecânicos de energia elétrica ativa. Faz-se uso de banco de dados de uma concessionária de energia elétrica e do processo de descoberta de conhecimento em bases de dados para selecionar as variáveis mais significativas na determinação de falhas em medidores eletromecânicos de energia elétrica ativa, incluindo no conjunto de falhas a operação com erros de medição acima do permitido pela legislação nacional (2010). Duas técnicas de mineração de dados foram utilizadas: regressão stepwise e árvores de decisão. As variáveis obtidas foram utilizadas na construção de um modelo de agrupamento de equipamentos associando a cada grupo uma probabilidade...
The operational reliability study of equipments has become primal in order to enterprises have the righteous control over their assets, both by financial side as by security reasons. The study for the hazard rate of equipments allows to foresee the failures for the equipments and to act preventively, but this study must be accomplished under established and fixed operation conditions. The energy meters, for their part, are equipments utilized in several operating conditions so on the utilization manner, like presence of harmonics, undervoltages and over-voltages and distinct consumption patterns, as on the installation location, like swel, temperature, humidity, etc. Failures in electromechanical Wh-meters are difficult to detect once that the majority of metering errors occurred mainly by aging of components do not change the quality of offered energy neither disrupt its supply. In this context, this work proposes a novel methodology to obtain failure determination for electromechanical Whmeters. It utilizes Wh-databases from an electrical company and of the process of knowledge discovery in databases to specify the most significant variables in determining failures in electromechanical Wh-meters, including in the failure set the operation with metering errors above those permitted by national regulations (2010). Two techniques of data mining were used in this work: stepwise regression and decision trees. The obtained variables were utilized on the construction of a model of clustering similar equipments and the probability of failure of those clusters were determined. As final results, an application in a friendly platform were developed in order to apply the methodology, and a case study was accomplished in order to demonstrate its feasibility.
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Sundström, Ebba, and Skagerlind Valentin Goodbrand. "Utvärdering av maskininlärningsmodeller för riktad marknadsföring inom dagligvaruhandeln." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-282927.
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Företag inom dagligvaruhandeln använder sig ofta av database marketing för att anpassa deras erbjudande till deras kunder och därmed stärka kundrelationen och ökaderas försäljning. Länge har logistisk regression varit en modell som ofta används för att bygga upp maskininlärningsmodeller som kan förutse vilka erbjudanden som löses in av vilken kund. I arbetet utvärderas en maskininlärningsmodell med logistisk regression och stepwise selection på kunddata från en av Sveriges större aktörer inom dagligvaruhandeln. Modellen jämförs med en annan modell som istället använder sig utav elastic net, vilket är en regulariserad regressionsmetod. Modellerna testas på fem olika produkter ur företagets sortiment och baseras på ett femtiotal variabler som beskriver kundernas sociodemografiska data och historiska köpbeteende i företagets butiker. Dessa utvärderas med hjälp av en förväxlingsmatris och värden för deras Accuracy, Balanced Accuracy, Precision, Recall och F1-score. Dessutom utvärderas modellen utifrån affärsnytta, påverkan på kundrelationer och hållbarhet. Studien visade att den logistiska regressionen med stepwise selection hade ett genomsnittligt värde för Precision på 23 procent. Vid användning av elastic net ökade värdet för Precision med i genomsnitt 7 procentenheter för samtliga modeller. Detta kan bero på att vissa av parametrarna i modellen med stepwise selection får överdrivet stora värden samt att stepwise selection väljer ut variabler för modellen som inte är optimala för att förutsäga kundens beteende. Det noterades även att kunder generellt verkade nöjda med de erbjudanden de fått, men missnöjda ifall de kände sig missförstådda av företaget.Companies within the FMCG trade often uses database marketing to customize offers to each customer, and thereby strengthen customer relationships to the company and increase their sales. For a long time, logistic regression has been the preferred machine modelling method to predict which offer to present to each costumer. This study evaluates a machinelearning model based on logistic regression and stepwise selection on costumer data from one of Sweden’s larger companies within the FMCG trade. The model is later compared to another model based on the elastic net-method, which is a regularized regressionmodel. The models are tested on five different products from the company’s assortment and are based on about fifty different variables which describes the costumers’ sociodemographic factors and purchasing history. The models are evaluated using a confusion matrix and values stating their Accuracy, BalancedAccuracy, Precision, Recall and F1-score. Furthermore, the model is evaluated in the perspectives of business advantages, costumer relations and sustainability. The study concluded that the logistic regression and stepwise selection-model had an average Precisionon 23 procent. When the elastic net-method was used the Precision increased with approximately 7 percentage points. This might depend on the fact that some of the parameters in the logistic regression-model had an overrated value and that the stepwise selection chose a subset of features that was not optimal to predict the consumer behaviour. It was also noted that costumers most often seemed content, but were dissatisfied if they felt misunderstood by the company.
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Vlack, Yvette A. "A Diffuse Spectral Reflectance Library of Clay Minerals and Clay Mixtures within the VIS/NIR Bands." Kent State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=kent1227006436.
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Mauk, Pheakdei. "Modélisation mathématique du micro-crédit." Phd thesis, Université Nice Sophia Antipolis, 2013. http://tel.archives-ouvertes.fr/tel-00942553.
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Le travail soumis commence par un aperçu du micro-crédit tel qu'il a été introduit au Bangladesh par M. Yunus. Puis on donne un modèle stochastique des retards de versement. Comme ces retards ne donnent pas lieu à une sanction financière, ils constituent, de fait, une baisse du taux réel de crédit. Ce taux est alors, lui-même, aléatoire. On calcule un taux espéré en fonction de la probabilité de retard de remboursement hebdomadaire. On déduit que ce taux espéré est d'environ 3.5% inférieur au taux (annoncé) du cas déterministe si l'on considère que 3% des retards atteignent 4 semaines. Le travail se poursuit par une étude statistique de données du micro-crédit en Thaïlande. On commence par présenter un modèle de régression logistique du taux de remboursement par rapport aux 23 variables mesurées sur un échantillon de 219 groupes d'emprunteurs. On présente ensuite une sélection des variables les plus pertinentes selon un critère AIC ou BIC par une méthode "backward stepwise". Finalement des expériences sur des sous-échantillons montrent une bonne stabilité du choix des variables obtenues par la sélection.
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Stine, Cory M. "Community College Trustee Orientation and Training Influence on Use of Best Practices." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1351125386.
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Di, Tullio Ian. "Improving the direct marketing practices of FMCG retailers through better customer selection : an empirical study comparing the effectiveness of RFM (Recency, Freuency and Monetary) CHAID (Chi-squared Automatic Interaction Detection), stepwise logit (logistic regression) and ANN (Artificial Neural Networks) techniques using different data variable depths." Thesis, Cranfield University, 2014. http://dspace.lib.cranfield.ac.uk/handle/1826/8837.
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The intent of this thesis is to understand Data Mining technique effectiveness in both shallow (RFM variable only) and expanded data environments. The thesis addresses two specific gaps in research: (1) the relationship between customer selection techniques and performance and (2) the effects of using different depths of data on performance. In shallow-data contexts stepwise logit and neural networks provided the greatest cumulative lift and outperformed both RFM and CHAID across all top deciles. However, RFM shows the second highest fit measure, illustrating its relative stability in predicting outcomes. In addition, the RFM technique performance was tested using both one-month and 12-month time series. The 12-month series performed better and showed a greater level of fit. The subsequent study comparing technique effectiveness under expanded variable sets demonstrated an even more significant and visible lift increase versus the RFM technique. Looking at logistic regression, CHAID and neural networks, the lifts and gains obtained at the first two deciles provide enough response lift to allow these techniques’ cumulative performance to surpass RFM well past decile five into decile six. From a cumulative perspective, the strong performance of logit and ANN allow these techniques to outperform CHAID in deciles one and two, but as of decile three, cumulative performance of all three advanced techniques becomes virtually identical. Though CHAID remains the technique with the best fit performance, RFM fit value falls to last place once an expanded variable set is introduced. Furthermore, both logistic and ANN performance increases significantly, and though they remain very close from an overall Gini and PCC score perspective, the logistic regression outperforms ANN when using expanded data. In both studies, dimensionality reduction plays a role in optimising model response. In limited data sets, logit applications reduced data to achieve better response, whereas in extended data sets, all models applied reductions. These findings contribute to the growing literature on customer selection techniques and provide a specific contribution to data mining, RM, segmentation and marketing practice by demonstrating how these techniques can be used for better consumer selection for purposes of customer development in FMCG retail.
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Kutluay, Umit. "Aerodynamic Parameter Estimation Using Flight Test Data." Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613786/index.pdf.
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This doctoral study aims to develop a methodology for use in
determining aerodynamic models and parameters from actual
flight test data for different types of autonomous flight vehicles.
The stepwise regression method and equation error method are utilized for the aerodynamic model identification and parameter estimation.
A closed loop aerodynamic parameter estimation approach is also applied in this study which can be used to fine tune the model parameters. Genetic algorithm is used as the optimization kernel for this purpose. In the optimization scheme, an input error cost function is used together with a final position penalty as opposed to widely utilized output error cost function.
Available methods in the literature are developed for and mostly applied to the aerodynamic system identification problem of piloted aircrafta very limited number of studies on autonomous vehicles are available in the open literature. This doctoral study shows the applicability of the existing methods to aerodynamic model identification and parameter estimation problem of autonomous vehicles. Also practical considerations for the application of model structure determination methods to autonomous vehicles are not well defined in the literature and this study serves as a guide to these considerations.
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Silva, Marcelo Rubia da. "Modelação e análise da vida útil (metrológica) de medidores tipo indução de energia elétrica ativa /." Ilha Solteira : [s.n.], 2010. http://hdl.handle.net/11449/87039.
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Orientador: Carlos Alberto CanesinBanca: Júlio Borges de Souza
Banca: Denizar Cruz Martins
Resumo: O estudo da confiabilidade operacional de equipamentos se tornou fundamental para as empresas possuírem o devido controle dos seus ativos, tanto pelo lado financeiro quanto em questões de segurança. O estudo da taxa de falha de equipamentos prevê quando as falhas irão ocorrer possibilitando estabelecer atitudes preventivas, porém, seu estudo deve ser realizado em condições de operação estabelecidas e fixas. Os medidores de energia elétrica, parte do ativo financeiro das concessionárias de energia, são equipamentos utilizados em diversas condições de operação, tanto nas condições do fluxo de energia, tais como presenças de harmônicos, subtensões, sobre-tensões e padrões de consumo distintos, quanto pelo local físico de instalação, tais como maresia, temperatura, umidade, etc. As falhas nos medidores eletromecânicos de energia elétrica são de difícil constatação uma vez que a maioria dos erros de medição, ocasionados principalmente por envelhecimento de componentes, não alteram a qualidade da energia fornecida e nem interrompem o seu fornecimento. Neste sentido, este trabalho propõe uma nova metodologia de determinação de falhas em medidores eletromecânicos de energia elétrica ativa. Faz-se uso de banco de dados de uma concessionária de energia elétrica e do processo de descoberta de conhecimento em bases de dados para selecionar as variáveis mais significativas na determinação de falhas em medidores eletromecânicos de energia elétrica ativa, incluindo no conjunto de falhas a operação com erros de medição acima do permitido pela legislação nacional (2010). Duas técnicas de mineração de dados foram utilizadas: regressão stepwise e árvores de decisão. As variáveis obtidas foram utilizadas na construção de um modelo de agrupamento de equipamentos associando a cada grupo uma probabilidade... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: The operational reliability study of equipments has become primal in order to enterprises have the righteous control over their assets, both by financial side as by security reasons. The study for the hazard rate of equipments allows to foresee the failures for the equipments and to act preventively, but this study must be accomplished under established and fixed operation conditions. The energy meters, for their part, are equipments utilized in several operating conditions so on the utilization manner, like presence of harmonics, undervoltages and over-voltages and distinct consumption patterns, as on the installation location, like swel, temperature, humidity, etc. Failures in electromechanical Wh-meters are difficult to detect once that the majority of metering errors occurred mainly by aging of components do not change the quality of offered energy neither disrupt its supply. In this context, this work proposes a novel methodology to obtain failure determination for electromechanical Whmeters. It utilizes Wh-databases from an electrical company and of the process of knowledge discovery in databases to specify the most significant variables in determining failures in electromechanical Wh-meters, including in the failure set the operation with metering errors above those permitted by national regulations (2010). Two techniques of data mining were used in this work: stepwise regression and decision trees. The obtained variables were utilized on the construction of a model of clustering similar equipments and the probability of failure of those clusters were determined. As final results, an application in a friendly platform were developed in order to apply the methodology, and a case study was accomplished in order to demonstrate its feasibility.
Mestre
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Plessner, Von Roderick. "A Study of the Influence Undergraduate Experiences Have onStudent Performance on the Graduate Management Admission Test." University of Toledo / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1401294447.
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Zielonka, Bronisława. "The Role of Linguistic Context in the Acquisition of the Pluperfect : Polish Learners of Swedish as a Foreign Language." Doctoral thesis, Stockholm University, Department of Scandinavian Languages, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-532.
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This work consists of two parts: the theoretical and the experimental. In the theoretical part, some general and some language specific theories of tense, aspect and aktionsart are presented, and the temporal systems of Swedish and Polish are compared.
The theoretical part is not a mere review of the literature on the subject. The comparison of the descriptions of aspect and aktionsart by Slavic researchers with the universal theory of Smith (1991) and (1977) and with description of aktionsart in Swedish in Teleman et al. (1999) has allowed me for some important observations as to the nature of the long-lasting dispute about the differences between aspect and aktionsart.
The experimental part is a cross-sectional study on the role of the linguistic context on the acquisition of the pluperfect by Polish learners Swedish as a foreign language. The informants are university students studying Swedish as a foreign language. The language samples were collected by means of two types of tests: gap-filling and translation from Polish.
Twelve linguistic factors, each divided into two subgroups, were hypothesised to have affected the correct use of the pluperfect. All those hypotheses as to which of the subgroups may inhibit and which may facilitate the correct use of the pluperfect are grounded in linguistic theories, i.e. presented in the form of linguistically-based discussions as to what kind of effect, facilitative or inhibiting, each of the linguistic factors may have had, and why.
The effect of those factors upon the correct use of the pluperfect has been tested by means of a step-wise multiple regression which measured the simultaneous effect of each factor upon the correct use of the pluperfect. This method has confirmed the facilitative effect of the following six linguistic factors: intrasentential indication of topic time (subordinate clause), unbounded verb indicating topic time, agentive meaning of the target verb, specifying subordinate clause, statal pluperfect and location of the time of action of pluperfect clause outside the temporal frame of narrative plot.
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Jobin, Erik. "An Urban Rainfall Storm Flood Severity Index." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/24124.
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Extreme rainfall statistics are important for the design and management of the water resource infrastructure. The standard approach for extreme rainfall event severity assessment is the Intensity-Duration-Frequency (IDF) method. However, this approach does not consider the spatial context of rainfall and consequently does not properly describe rainfall storm severity, nor rarity. This study provides a critical account of the current standard practice and presents an approach that takes into consideration both the spatial context of rainfall storms, and indirectly incorporates runoff to produce a representative approach to assessing urban rainfall storm severity in terms of flood potential. A stepwise regression analysis was performed on a dataset of individual rainfall storm characteristics to best represent documented basement floodings in the City of Edmonton. Finally, the urban rainfall storm flood severity index was shown to be most representative of the documented basement floodings' severity when compared to that of the IDF method.
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Wu, Tay Fang, and 吳泰芳. "Estimation of Change-Points Using Statistical Regression Stepwise Methods." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/04980461814353523097.
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碩士國立中興大學
應用數學系
87
In recent years, the statistical literature about the problem of the detection of change-points is really discussed widely. Now, we will explore a special and distinct form of the problem of detecting change-points. Here the Change-Point Model is similar to the general multiple regression model, and our main problem is to estimate and find the locations of change-points. The idea is that we assume that every point is a change-point, and we will use statistical regression stepwise methods to identify the true change-points and remove the false change-points. Therefore, by using statistical regression stepwise methods such as backward elimination procedure, forward selection procedure and stepwise regression procedure, we will obtain the quick and accurate estimates of the parameters of the change-point model, and the results of a Monte Carlo simulation study are presented to demonstrate the favorable estimation which is the final goal we want to accomplish.
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Jan, Wafaa Omar. "Testing a Conceptual Model of Three Key Strengths of Psychosocial Well-being in Saudi Gifted Adolescents." Thesis, 2017. https://vuir.vu.edu.au/42160/.
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The important role of psychosocial well-being in increasing the manifestation of intellectual giftedness in adolescents is evident in the literature. In this thesis three psychological perspectives have provided the theoretical background for the development of a conceptual model of the psychosocial well-being in adolescents:
1. Psychosocial theory relating psychosocial development in adolescence to the successful resolution of identity crisis in the form of the ego strength of fidelity.
2. The social cognitive identity style model which adds additional insight into the identity function of adolescents as processing self-relevant information about self and constructing self-identity.
3. The constructive-developmental theory that refers to complexity of mind as a means of understanding the mental health of adolescents.
The major aim of this thesis was to examine the usefulness of the conceptual model as
a construct of the three key strengths to explore the psychosocial well-being in Saudi gifted adolescents. The usefulness of the conceptual model of psychosocial well-being in Saudi intellectually gifted adolescents was examined using a two stages approach. The first stage investigated the conceptual relationship between identity style and psychosocial ego strengths with 226 Saudi gifted high school students. The sample comprised 134 males and 132 females, ranging in age from 15 to 17.
Identity style and psychosocial ego strengths were assessed using two validated instruments. Markstrom’s Psychosocial Inventory of Ego Strengths (PIES) was developed to measure Erikson’s eight ego strengths (hope, will, purpose, competence, fidelity, love, care, and wisdom). Berzonsky’s Identity Style Inventory (ISI-3) was used to measure three styles of identity processing orientation: the informational, normative and diffuse-avoidant styles. Both instruments were translated in Arabic.
Analysis was undertaken using statistical tests including ANOVA and stepwise regressions to test whether males and females differed in the use of three identity styles, and to test the relationships between identity style and the total PIES score and the PIES subscale fidelity as associated with the positive resolution of identity crisis in adolescence. Recruited from Stage 1, 18 structured interviews were undertaken in Stage 2. These interviews followed the Structure of Subject- Object Interview (SOI) procedure and analytic structure developed by Lahey, Souvaine, Kegan, Goodman and Felix in 1990.
Gender differences were examined for the three identity styles of processing (ISI-3) and the eight ego strengths subscales. Both males and females used all three identity styles; however, the males scored significantly higher on the information and normative styles than the females whereas females scored higher on the diffuse/avoidant styles. For the PIES, females scored higher than males on the subscales of love and care. There were no significant differences for the other six subscales.
Stepwise linear regression was used to assess the relative contribution of the three identity styles and gender to the PIES total score, and for the PIES subscale fidelity. Informational style accounted for 14% of the variation in the PIES total score. The diffuse– avoidant style was negatively associated with the PIES total score and gender was significant. 23 percent of the variance in the PIES total score was explained by these three variables. All ISI-3 styles and gender were significantly associated with the Fidelity sub-scale, with approximately 17% of the variance explained.
The findings of the Subject–Object Interview (SOI) analysis, which focused on complexity of mind, were limited as all participants showed no evidence of higher order of mental capacity more than the socialized mind among all three identity styles.
The conceptual model has confirmed the relationships between the social cognitive processing self-relevant information and the psychosocial ego development. The psychosocial health among intellectually gifted adolescents can be understood through the identity styles as functional aspects of psychosocial well-being. The complexity of mind explains the order of mental capacity among intellectually gifted adolescents.
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Lu, Chung-You, and 盧重佑. "A Study of Learning Satisfaction in Education Using Stepwise Regression." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/01646162103366632928.
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碩士明道大學
管理研究所
96
This research aims at learning satisfaction in college. First, analyze the background of the case school in the literature review, and analyze the factors and their relations. The factors to the learning satisfaction were divided into three groups: school, teacher, and the student. Gender and grade were set as the intervening variables, according to the case school background, to do the survey. A questionnaire survey was conducted in this research to understand the relationships between school factor, teacher factor, student factor and the learning satisfaction degree. From the analysis within completed questionnaires, the importance of influence from teaching material, lecture quality and interpersonal relation was reemphasized. Finally, the research gave suggestion to the school for their administration reference according to the research conclusion in each phase.
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Chan, Chiao-Wei, and 詹巧薇. "Building real estate valuation models with stepwise decomposition regression analysis." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/66770503789092335845.
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碩士淡江大學
土木工程學系碩士班
102
Multivariate regression analysis is usually employed to establish real estate valuation formula. This approach is quite simple, but it has a few drawbacks including being difficult to understand the meaning of the coefficients, cannot be universal to another areas, cannot be used in comparison approach, and without good flexibility. The purpose of this study is to propose the stepwise decomposition regression analysis to overcome these shortcomings. The factors considered in this study include The factor of the distance to the nearest MRT station which represents the impact of transportation function to the price per unit area. The factor of the number of convenience stores in the living circle on foot which represents the impact of living function to the price per unit area. The factor of the age of house which represents the impact of the quality of the house to the price per unit area. The factor of transaction date which represents the impact of market trend to the price per unit area. The factor of the geographic coordinates which represent the impact of spatial location to the price per unit area. The results showed that the 20% error hit rates of real estate valuation were greater than 70% for all the four testing areas in Taipei City and New Taipei City.
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Lai, chung yei, and 賴聰毅. "Estimation of Parameters in a Multipath Signal Using Regression Stepwise Procedures." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/35487456768019525294.
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Chen, Hong-Rong, and 陳宏榮. "Assessment of Lifting Formulations Developed by Neural Network and Stepwise Regression." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/59206827148230959258.
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碩士華梵大學
工業工程與經營資訊學系碩士班
101
Many previous studies related to manual material handling tasks applied the traditional method of linear regression to establish the forecasting model of lifting capacity (maximal acceptable weight of lift, MAWL). Unfortunately, the predictability (R2) of the lifting capacity models are low. Therefore, the stepwise regression and back-propagation neural network (BPNN) were applied to model lifting capacity in this study. There are five predictor variables, asymmetric, vertical travelling distance, handle angle, stature and body weight in each lifting capacity model. For the BPNN, two transfer functions, LOGSIG and PURELIN, were chosen to establish model respectively. The results show that using the GMDH algorithms get the highest R2 (0.82), followed by the BPNN with PURELIN transfer function R2 (0.7252), followed by the traditional method of linear regression (R2=0.6908), and the lowest R2 (0.402) appears at the BPNN with LOGSIG transfer function. In this study, the best predictive model is shown as follows: The detailed information of this model’s parameters are summarized as follows: asy(X1): lifting symmetry, from 0 ° to 90 °; angle(X2): handle angle , from 0 ° to 90 °; frequency(X3): lifting frequency,1 time of 1 minute and 4 times of 1 minute; dist(X4): vertical travelling distance, from knuckle height to shoulder height; stature(X5): a subject’s height; weight(X6): a subject’s body weight. Keywords: Lifting Capacity Forecasting Model, Neural Networks, Back-Propagation Networks, Stepwise Regression
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Docter, William A. "Order reduction of nonlinear dynamic models by subspace identification and stepwise regression /." Diss., 1999. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:9935158.
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Peng, Kuang-Jeng, and 彭光正. "Use the regression tree and stepwise regression to build a multi-factor model of stock selection in Taiwan." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/46169006130963958443.
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碩士中華大學
資訊管理學系(所)
98
After combining many effects, we can construct a stock selection model with higher return, but it is clearly inefficient using trial and error method to find the best multi-factor model. This study took Sorting Normalization Method to normalize the independent variables and the dependent variable. On the modeling method, since only some factors influence the stock selection, an over-complex multi-factor model will fall into the trap of data snooping and will only build a repetition model, not a generalization model. Therefore, the study employed the stepwise regression and regression tree to build stock selection models. To evaluate the accuracy of these models, the study took an empirical analysis on the Taiwan stock market. Conclusions are given as follows. (1) From the 12 factors considered, stepwise regression selected two most important factors, the return on equity (ROE) and price-to-book value ratio (PBR). These two factors could explain more than 80% variance. (2) According to the estimation of stepwise regression, the best weight of ROE and the best weight of PBR are respectively 55% and 45%. Empirical results showed that the weights are close to the best one. (3) Regression trees showed that after-tax earnings per share, PE ratio, and PBR are the most important factors. Although we didn’t find that ROE was one of the most important factors, but the rule set generated by the regression trees implied that the higher the ROE, the higher the return. (4) The empirical results showed that the rules with the highest and lowest predicted return generated by regression trees achieved the highest and lowest return among all the rules, which showed that the regression tree can produce useful stock-picking rules.
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Cheng, Kuan-Chih, and 鄭光智. "Constructing a Feedback System Between Production and Metrology Tools using Stepwise Regression and GMDH." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/18284429173516214810.
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Gu, Xiangjun Rosner Gary Daiger Stephen Chan Wenyaw. "Stepwise forward multiple regression for complex traits in high density genome-wide association studies." 2007. http://proquest.umi.com/pqdweb?did=1417801171&sid=11&Fmt=2&clientId=68716&RQT=309&VName=PQD.
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Thesis (Ph. D.)--University of Texas Health Science Center at Houston, School of Public Health, 2007.Source: Dissertation Abstracts International, Volume: 68-10, Section: B, page: 6419. Advisers: Christopher I. Amos; Ralph F. Frankowski. Includes bibliographical references.
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Chi, Shao-Chun, and 紀少淳. "A Study on Credit Spreads of Corporate Bonds in Taiwan Using the Stepwise Regression Method." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/29943678510380986254.
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碩士國立臺灣大學
財務金融學研究所
97
This thesis attempts to find the key determinants of credit spreads in Taiwanese bond market. Liquidity risk, time to maturity, stock market information, interest rate, and the financial ratios are considered in the model. The stepwise regression method is used to analyze credit spreads. In this thesis, the regression results for each variable show that time to maturity and interest are significantly correlated to credit spreads for most of the companies. The stepwise regression results in this thesis also show that liquidity risk, time to maturity, and interest rate are selected in the models of most companies. Both regression results and stepwise regression results in this thesis show that the stock market information is not important in explaining credit spreads.
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Lee, Yu-Chia, and 李友嘉. "An Empirical Study on Stepwise Regression,Reality Check and Superior Predictive Ability-Evidence from TAIEX." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/40887508297817139846.
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碩士國立中興大學
應用數學系所
95
The return is very complicated and hard to predict in the financial market. This article uses common technical analysis-momentum, trend line, relative strength index, moving average and some sentiment indicators -volatility index, put call ratio of open interest, put call ratio of volume to be variables of regression model. Moreover, we apply reality check (White, 2000), test for superior predictive ability (Hansen, 2005) and stepwise regression to select useful variables. We hope to find useful variables and provide more correct infromation in the financial markets. Sentiment indicators are useful in this article.
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Chen, Barlar, and 陳文彰. "Effect of Incorrect Prior Information of Known Points on Stepwise Regression Adjustment Results of Densification Networks." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/62293168089041146381.
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碩士國立成功大學
測量工程學系
88
The incorrect prior information of known points could have the effect on the estimates of coordinates and their covariance matrix of densification networks. In this paper, the mathematical expressions by the stepwise regression with incorrect prior information are presented, and the influence of incorrect prior information of known points is investigated by numerical examples. To maintain the exterior accuracy, the new points of densification networks must connect to the neighboring known points. But the connection to known points of the more high order may cause the extra incorrect prior information from theoretical point of view, if the stepwise regression is used. For analyzing the influence, the numerical results of some leveling networks by stepwise regression are compared with those by the rigorous adjustment and by the hierarchical adjustment. The advantage of the three different adjustment methods is also discussed. Finally, a new adjustment procedure of densification networks is suggested.
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You, Jin-An, and 游謹安. "Applying Stepwise Regression, Decision Tree, Rough Set Theory, and Artificial Neural Network for Detecting Fraud of Enterprises." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/e8682y.
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碩士中國文化大學
會計學系
102
More and more frauds have occurred in recent years. When corporations involve in critical frauds, the corporation itself and investors suffer from all such frauds. As a result, the society incurs huge costs in order to make up for the loss caused by the frauds. Most of the fraud-related literatures studied frauds using the conventional re-gression model. In recent years, however, many researchers detected frauds using data mining method with satisfactory accuracy. However, not enough literatures are available at this moment. Therefore, this study attempted to identify critical variables using the conven-tional stepwise regression method, the Chi-square automatic Interaction Detection (CHAID) designed for data mining, as well as rough set. This study adopted financial variables and non-financial variables in order to construct an effective tool to detect frauds. Moreover, this study focused on 41 enterprises involved in corporate frauds and 123 enterprises not involved in corporate frauds in 2003-2013. According to the research results, the fraud detection model constructed with ar-tificial neural network together with rough set is sufficient to detect fraud for auditors, and is a perfect tool for the auditors and investors whenever they have to reach major decisions.