To see the other types of publications on this topic, follow the link: Method of correlation–regression analysis.
Dissertations / Theses on the topic 'Method of correlation–regression analysis'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Method of correlation–regression analysis.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
1
Park, Soyoun. "Penalized method based on representatives and nonparametric analysis of gap data." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37307.
Full textAbstract:
When there are a large number of predictors and few observations, building a regression model to explain the behavior of a response variable such as a patient's medical condition is very challenging. This is a "p ≫n " variable selection problem encountered often in modern applied statistics and data mining. Chapter one of this thesis proposes a rigorous procedure which groups predictors into clusters of "highly-correlated" variables, selects a representative from each cluster, and uses a subset of the representatives for regression modeling. The proposed Penalized method based on Representatives (PR) extends the Lasso for the p ≫ n data and highly correlated variables, to build a sparse model practically interpretable and maintain prediction quality. Moreover, we provide the PR-Sequential Grouped Regression (PR-SGR) to make computation of the PR procedure efficient. Simulation studies show the proposed method outperforms existing methods such as the Lasso/Lars. A real-life example from a mental health diagnosis illustrates the applicability of the PR-SGR. In the second part of the thesis, we study the analysis of time-to-event data called a gap data when missing time intervals (gaps) possibly happen prior to the first observed event time. If a gap occurs prior to the first observed event, then the first observed event may or may not be the first true event. This incomplete knowledge makes the gap data different from the well-studied regular interval censored data. We propose a Non-Parametric Estimate for the Gap data (NPEG) to estimate the survival function for the first true event time, derive its analytic properties and demonstrate its performance in simulations. We also extend the Imputed Empirical Estimating method (IEE), which is an existing nonparametric method for the gap data up to one gap, to handle the gap data with multiple gaps.
2
Jankech, Aleš. "Vliv přítomnosti zeleně na cenu nemovitostí." Master's thesis, Vysoká škola ekonomická v Praze, 2009. http://www.nusl.cz/ntk/nusl-15812.
Full textAbstract:
My Diploma thesis is focused on economic evaluation of gratuitous goods, especially on hedonic price method. The core of this paper is theoretical description and practical usage of HPM. Main theme is "Influence of plantscape on flat price.
3
Andersson, Gustaf. "Generalised linear factor score regression : a comparison of four methods." Thesis, Uppsala universitet, Statistiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-412851.
Full textAbstract:
Factor score regression has recently received growing interest as an alternative for structural equation modelling. Two issues causing uncertainty for researchers are addressed in this thesis. Firstly, more knowledge is needed on how different approaches to calculating factor score estimates compare when estimating factor score regression models. Secondly, many applications are left without guidance because of the focus on normally distributed outcomes in the literature. This thesis examines how factor scoring methods compare when estimating regression coefficients in generalised linear factor score regression. An evaluation is made of the regression, correlation-preserving, total sum, and weighted sum method in ordinary, logistic, and Poisson factor score regression. In contrast to previous studies, both the mean and variance of loading coefficients and the degree of inter-factor correlation are varied in the simulations. A meta-analysis demonstrates that the choice of factor scoring method can substantially influence research conclusions. The regression and correlation-preserving method outperform the other two methods in terms of coefficient and standard error bias, accuracy, and empirical Type I error rates. Moreover, the regression method generally has the best performance. It is also noticed that performance can differ notably across the considered regression models.
4
Lacko, Matej. "Analýza ekonomických ukazatelů vybrané firmy pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2018. http://www.nusl.cz/ntk/nusl-378337.
Full textAbstract:
The diploma thesis deals with the analysis of economic indicators of Technos a.s., using statistical methods and the evaluation of the current financial situation. The work contains a theoretical and practical part. The theoretical part describes selected economic indicators, regression analysis, time series and correlation analysis. In the practical part, the analysis of selected economic indicators will be carried out and then statistical methods will be used to determine the prediction for the next year and to reveal the dependence between the individual indicators. The last part of the thesis deals with proposals that will improve the financial situation of the company.
5
Shalaginova, Daria. "Posouzení vybraných ukazatelů společnosti pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2020. http://www.nusl.cz/ntk/nusl-414494.
Full textAbstract:
Master’s thesis is aimed at assessing the selected financial indicators of the company using statistical methods. Based on the results, the current situation of the company is evaluated. The thesis consists of three parts. The first part contains the necessary theoretical bases for processing the analytical part. The second part is devoted to the analysis of selected indicators, which are then applied statistical methods to the prediction of the future development of these indicators and findings, here between these indicators there is a dependence. At the end of this part, there is an evaluation of the analyzed indicators. The third part presents appropriate proposals for solutions to existing problems caused by indicators that deviate from the recommended values.
6
Šebestová, Monika. "Posouzení finanční výkonnosti podniku pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2014. http://www.nusl.cz/ntk/nusl-224470.
Full textAbstract:
The master’s thesis deals with the assessment of the financial performance of a company using statistical methods. The theoretical part describes the problems of time series, regression analysis, correlation analysis and financial analysis. In the practical part statistical methods are used to reveal the dependence between the indicators and the prediction of the future development of the company in the coming years. On the basis of established results the company is compared with two important rivals, and there are made some suggestions how to improve its economic situation.
7
Rešková, Petra. "Posouzení vybraných ukazatelů společnosti pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2020. http://www.nusl.cz/ntk/nusl-414492.
Full textAbstract:
Master´s thesis deals with the assessment of selected financial indicators of the company using a statistical methods. The first part is focused on the theoretical description of financial indicators, time series analysis as well as regression and correlation analysis. The practical part contains a statistical analysis of selected indicators with subsequent prediction of indicators for the next two years. The practical part also contains a comparison of selected indicators with the industry average and a correlation analysis to determine the dependence of selected indicators. The last part contains suggestions to improve the situation of the company.
8
Bednářová, Veronika. "Posouzení vybraných ukazatelů společnosti pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2021. http://www.nusl.cz/ntk/nusl-443126.
Full textAbstract:
The diploma thesis is focused on the assessment of selected indicators using statistical methods. The first part is devoted to theoretical background, which describes financial indicators, time series analysis and regression and correlation analysis. The second part deals with the analysis of selected indicators and statistical analysis, which predicts the values of indicators for the next two years. Then correlation analysis is created, which determines the dependence between selected financial indicators. The last part is devoted to proposals leading to the improvement of the current situation of the company.
9
Hofmanová, Aneta. "Posouzení vybraných ukazatelů společnosti pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2018. http://www.nusl.cz/ntk/nusl-377969.
Full textAbstract:
Master's thesis deals with the assessment of selected financial indicators of the company through a financial analysis and statistical methods, on the basis of which then evaluates the current situation of the company. The thesis is divided into three parts. The theoretical part contains the issues necessary for the analytical part. The analytical part is focused on the analysis of selected indicators and the subsequent application of statistical methods to predict their future development and to detect dependencies between the indexes. The last part formulates possible solutions to problems caused by financial indicators that do not reach the required values.
10
Johanides, Petr. "Posouzení vybraných ukazatelů firmy pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2016. http://www.nusl.cz/ntk/nusl-241622.
Full textAbstract:
Master’s thesis assesses the financial and economic situation of the joint-stock company Composite Components. There are theoretical aspects including financial, regression and correlation analysis in the first part of the thesis. Financial indicators are computed and then subjected to the mentioned analyses in order to get prognoses for following years. The created suggestions which are in the end of the thesis are based on the indicators and prognoses.
11
Pastyřík, Jaroslav. "Posouzení výkonnosti firmy pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2015. http://www.nusl.cz/ntk/nusl-225066.
Full textAbstract:
The master’s thesis deals with the evaluation of financial efficiency of the company Bučovice Tools, a.s. using statistical methods. The theoretical part describes financial analysis, time series analysis, regression analysis and correlation analysis. In the practical part, the selected indicators of financial analysis are subjected to statistical analysis to detect dependence between indicators and to determine the prediction of the future development. Based on the financial results, the company is compared with a chosen company and with average indicators of the industry and are designed possibilities to improve the economic situation.
12
Herčková, Simona. "Posouzení výkonnosti firmy pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2016. http://www.nusl.cz/ntk/nusl-241173.
Full textAbstract:
The master’s thesis deals with the assessment of the financial performance of the company using statistical methods. The theoretical part describes the issues necessary for the practical part, financial indicators, time series, regression analysis and correlation analysis. In the practical part of the work is a calculation of selected financial indicators, then statistical methods are used to predict future developments and to detect dependencies between the indexes. The last section contains suggestions for improving the current situation.
13
Petrová, Veronika. "Posouzení výkonnosti akciové společnosti pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2018. http://www.nusl.cz/ntk/nusl-378000.
Full textAbstract:
The master´s thesis deals with theassesment of financial performance of YXZ, a. s. using statistical methods. The theoretical part describes the issues necessary for the practical part, financial indicators, time series, regression and correlation analysis. The analytical part analyzes selected financial indicators, then statistical methods are used to predict future development for the coming two years and to detect dependencies between the indexes. The last part of the thesis contains suggestions for improving the company's existing financial efficiency based on the calculations from the practical part.
14
Matys, Jan. "Posouzení ekonomické situace společnosti a návrhy na její zlepšení." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2019. http://www.nusl.cz/ntk/nusl-402020.
Full textAbstract:
The diploma thesis evaluates the economic situation of BPS Bicycle Industrial s. r. o. time series analysis. The theoretical part describes financial indicators, time series analyzes and regression and correlation analysis. Based on the analyzes, suggestions were made to improve the current situation of the company. BPS has proven to be financially sound. Shortcomings to improvement were identified from the analyzes. For example, share of equity and debt, use of surplus funds and turnover of receivables and payables. This ratio needs to be addressed through greater use of debt. The system of sanctions is solution for problem the turnover of receivables and the use of surplus funds by investing in shares.
15
Chen, Xi. "Learning with Sparcity: Structures, Optimization and Applications." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/228.
Full textAbstract:
The development of modern information technology has enabled collecting data of unprecedented size and complexity. Examples include web text data, microarray & proteomics, and data from scientific domains (e.g., meteorology). To learn from these high dimensional and complex data, traditional machine learning techniques often suffer from the curse of dimensionality and unaffordable computational cost. However, learning from large-scale high-dimensional data promises big payoffs in text mining, gene analysis, and numerous other consequential tasks.
Recently developed sparse learning techniques provide us a suite of tools for understanding and exploring high dimensional data from many areas in science and engineering. By exploring sparsity, we can always learn a parsimonious and compact model which is more interpretable and computationally tractable at application time. When it is known that the underlying model is indeed sparse, sparse learning methods can provide us a more consistent model and much improved prediction performance. However, the existing methods are still insufficient for modeling complex or dynamic structures of the data, such as those evidenced in pathways of genomic data, gene regulatory network, and synonyms in text data.
This thesis develops structured sparse learning methods along with scalable optimization algorithms to explore and predict high dimensional data with complex structures. In particular, we address three aspects of structured sparse learning:
1. Efficient and scalable optimization methods with fast convergence guarantees for a wide spectrum of high-dimensional learning tasks, including single or multi-task structured regression, canonical correlation analysis as well as online sparse learning.
2. Learning dynamic structures of different types of undirected graphical models, e.g., conditional Gaussian or conditional forest graphical models.
3. Demonstrating the usefulness of the proposed methods in various applications, e.g., computational genomics and spatial-temporal climatological data. In addition, we also design specialized sparse learning methods for text mining applications, including ranking and latent semantic analysis.
In the last part of the thesis, we also present the future direction of the high-dimensional structured sparse learning from both computational and statistical aspects.
16
Dargis, Evaldas. "Statistinių metodų taikymas tyrimo rezultatams apdoroti." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2011. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20110804_094737-09571.
Full textAbstract:
Šiame darbe pateikta nuosekli statistinės analizės metodika tyrimo rezultatams apdoroti ir nagrinėjamos kriterijų taikymo galimybės. Pasiūlyti kriterijai ryškiai išsiskiriantiems duomenims atmesti, nurodyti kriterijai tyrimo rezultatų atsitiktinumui ir nepriklausomumui bei pasiskirstymo pagal normalųjį dėsnį hipotezėms tikrinti, atlikta tyrimo rezultatų koreliacinė ir regresinė analizė ir pasirinkto regresinio modelio adekvatumo tikrinimas panaudojus Fišerio kriterijų.<br>The paper provided a consistent statistical analysis techniques to process the results of the study and analyze the possibility of application of the criteria. Propose criteria for emissions during the data significantly rejected by the criteria set out in the survey results to chance and the independence of the distribution under the normal law of hypotheses to verify the results of research carried out correlation and regression analysis and the selected regression model for testing the adequacy of using the Fisher criterion.
17
Čupr, Jiří. "Uplatnění statistických metod při zpracování dat." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2016. http://www.nusl.cz/ntk/nusl-241174.
Full textAbstract:
This master's thesis is focused on problem of orders of ingredients in McDonald's. It's an analysis of usage changes depending on outside temperature. Thesis includes theoretical background for correct analysis of the problem and possibilities to figuring it out. There is also an algorithmus for more efficient solution of problem with needs or excess of ingredients. There is also a program written in VBA language, that makes more simple usage of this algorithm on restaurants.
18
Urbášková, Martina. "Hodnocení vlivu větrných elektráren na krajinný ráz." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-114006.
Full textAbstract:
The goal of the work is to provide monetary valuation of changes in visual aspects of the landscape as a result of construction of an additional wind turbine in the village Maletín. For a suitable method for achieving the goal is being selected the contingent valuation method. A key element of this method is being considered the carefully compiled questionnaire, on which basis is made the quantification and evaluation of collected data. The representative sample consists of 112 households and the selected payment method is the increase of the monthly bill for electricity. The questionnaire reports that 54.3% of households consider the impact of wind turbines on the landscape Maletín to be positive. With the construction of additional wind turbine agree less than 74.3% of households and the most common reason is to obtain grants for the village and to produce cleaner energy from wind turbines. With the construction of new wind turbine while increasing monthly bill agrees 28.6% of all households living in the village Maletín. Estimation of changes in a welfare, thus improving the quality of the environment, is based on estimated central values, that has been calculated from selected characteristics and nonparametric estimation. The average household's willingness to pay for construction of wind turbine is estimated to be between 77 CZK - 200 CZK per month.
19
Chen, I.-Chen. "Improved Methods and Selecting Classification Types for Time-Dependent Covariates in the Marginal Analysis of Longitudinal Data." UKnowledge, 2018. https://uknowledge.uky.edu/epb_etds/19.
Full textAbstract:
Generalized estimating equations (GEE) are popularly utilized for the marginal analysis of longitudinal data. In order to obtain consistent regression parameter estimates, these estimating equations must be unbiased. However, when certain types of time-dependent covariates are presented, these equations can be biased unless an independence working correlation structure is employed. Moreover, in this case regression parameter estimation can be very inefficient because not all valid moment conditions are incorporated within the corresponding estimating equations. Therefore, approaches using the generalized method of moments or quadratic inference functions have been proposed for utilizing all valid moment conditions. However, we have found that such methods will not always provide valid inference and can also be improved upon in terms of finite-sample regression parameter estimation. Therefore, we propose a modified GEE approach and a selection method that will both ensure the validity of inference and improve regression parameter estimation.
In addition, these modified approaches assume the data analyst knows the type of time-dependent covariate, although this likely is not the case in practice. Whereas hypothesis testing has been used to determine covariate type, we propose a novel strategy to select a working covariate type in order to avoid potentially high type II error rates with these hypothesis testing procedures. Parameter estimates resulting from our proposed method are consistent and have overall improved mean squared error relative to hypothesis testing approaches.
Finally, for some real-world examples the use of mean regression models may be sensitive to skewness and outliers in the data. Therefore, we extend our approaches from their use with marginal quantile regression to modeling the conditional quantiles of the response variable. Existing and proposed methods are compared in simulation studies and application examples.
20
Kožariková, Veronika. "Hodnotenie environmentálneho statku - východoslovenská priehrada Ružín." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-73872.
Full textAbstract:
The main purpose of the diploma thesis is to determine the willingness of people visiting the Eastern Slovak dam Ružín to pay for improving water quality, namely for the environmental good. Willingness to pay is determined by questionnaire investigation the contingent valuation method. Dam is a public good, which has no owner. We all use it without someone to care for it. This use is not positive, but negative in terms of pollution, clogging of toxic sediments. The theoretical part is devoted to construction and the need to build dam as well as environmental problems, which occur at the dam. This is related to the problem of public good and "the tragedy of the commons." There are the contingent valuation method and development of the questionnaire described at the end of theoretical part. The practical part consists of the evaluation questionnaire investigation and the linear regression model in terms of the parameters under which they were created identifiers variables and point estimates. Finally, it is converted by statistical analysis of the impact of variables on the amount that people are willing to pay.
21
Travencová, Darina. "Posouzení vybraných ukazatelů pomocí analýzy časových řad." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2017. http://www.nusl.cz/ntk/nusl-318310.
Full textAbstract:
The master´s thesis evaluates the economic situation of the company SCHWARTZ TECHNICKÉ PLASTY ČR s. r. o. using statistical methods. The theoretical part describes the issues necessary for the practical part, financial indicators, time series, regression and correlation analysis. In the practical part is an analysis of selected indicators of financial analysis, then statistical methods are used to predict future developments for the coming two years and to detect dependencies between the indexes. The last section contains suggestions for improving the current situation, which are based on calculations from the practical part.
22
Sullwald, Wichard. "Grain regression analysis." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86526.
Full textAbstract:
Thesis (MSc)--Stellenbosch University, 2014.<br>ENGLISH ABSTRACT: Grain regression analysis forms an essential part of solid rocket motor simulation.
In this thesis a numerical grain regression analysis module is developed
as an alternative to cumbersome and time consuming analytical methods. The
surface regression is performed by the level-set method, a numerical interface
advancement scheme. A novel approach to the integration of the surface area
and volume of a numerical interface, as defined implicitly in a level-set framework,
by means of Monte-Carlo integration is proposed. The grain regression
module is directly coupled to a quasi -1D internal ballistics solver in an on-line
fashion, in order to take into account the effects of spatially varying burn rate
distributions. A multi-timescale approach is proposed for the direct coupling
of the two solvers.<br>AFRIKAANSE OPSOMMING: Gryn regressie analise vorm ’n integrale deel van soliede vuurpylmotor simulasie.
In hierdie tesis word ’n numeriese gryn regressie analise model, as ’n alternatief
tot dikwels omslagtige en tydrowende analitiese metodes, ontwikkel.
Die oppervlak regressie word deur die vlak-set metode, ’n numeriese koppelvlak
beweging skema uitgevoer. ’n Nuwe benadering tot die integrasie van die
buite-oppervlakte en volume van ’n implisiete numeriese koppelvlak in ’n vlakset
raamwerk, deur middel van Monte Carlo-integrasie word voorgestel. Die
gryn regressie model word direk en aanlyn aan ’n kwasi-1D interne ballistiek
model gekoppel, ten einde die uitwerking van ruimtelik-wisselende brand-koers
in ag te neem. ’n Multi-tydskaal benadering word voorgestel vir die direkte
koppeling van die twee modelle.
23
Скворчевський, Олександр Євгенович, Тетяна Кравцова та Анастасія Свічкарь. "Економетрична оцінка залежності купівельної спроможності населення України від його доходів". Thesis, Львівська політехніка, 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/32787.
Full text
24
Lei, Song. "Informative correlation extraction from and for Forex market analysis." AUT University, 2010. http://hdl.handle.net/10292/899.
Full textAbstract:
The forex market is a complex, evolving, and a non-linear dynamical system, and its forecast is difficult due to high data intensity, noise/outliers, unstructured data and high degree of uncertainty. However, the exchange rate of a currency is often found surprisingly similar to the history or the variation of an alternative currency, which implies that correlation knowledge is valuable for forex market trend analysis. In this research, we propose a computational correlation analysis for the intelligent correlation extraction from all available economic data. The proposed correlation is a synthesis of channel and weighted Pearson's correlation, where the channel correlation traces the trend similarity of time series, and the weighted Pearson's correlation filters noise in correlation extraction. In the forex market analysis, we consider 3 particular aspects of correlation knowledge: (1) historical correlation, correlation to previous market data; (2) cross-currency correlation, correlation to relevant currencies, and (3) macro correlation, correlation to macroeconomic variables. While evaluating the validity of extracted correlation knowledge, we conduct a comparison of Support Vector Regression (SVR) against the correlation aided SVR (cSVR) for forex time series prediction, where correlation in addition to the observed forex time series data is used for the training of SVR. The experiments are carried out on 5 futures contracts (NZD/AUD, NZD/EUD, NZD/GBP, NZD/JPY and NZD/USD) within the period from January 2007 to December 2008. The comparison results show that the proposed correlation is computationally significant for forex market analysis in that the cSVR is performing consistently better than purely SVR on all 5 contracts exchange rate prediction, in terms of error functions MSE, RMSE, NMSE, MAE and MAPE. However, the cSVR prediction is found occasionally differing significantly from the actual price, which suggests that despite the significance of the proposed correlation, how to use correlation knowledge for market trend analysis remains a very challenging difficulty that prevents in practice further understanding of the forex market. In addition, the selection of macroeconomic factors and the determination of time period for analysis are two computationally essential points worth addressing further for future forex market correlation analysis.
25
Twagirumukiza, Etienne. "Analysis of Faculty Evaluation by Students as a Reliable Measure of Faculty Teaching Performance." Digital Archive @ GSU, 2011. http://digitalarchive.gsu.edu/math_theses/105.
Full textAbstract:
Most American universities and colleges require students to provide faculty evaluation at end of each academic term, as a way of measuring faculty teaching performance. Although some analysts think that this kind of evaluation does not necessarily provide a good measurement of teaching effectiveness, there is a growing agreement in the academic world about its reliability. This study attempts to find any strong statistical evidence supporting faculty evaluation by students as a measure of faculty teaching effectiveness. Emphasis will be on analyzing relationships between instructor ratings by students and corresponding students’ grades. Various statistical methods are applied to analyze a sample of real data and derive conclusions. Methods considered include multivariate statistical analysis, principal component analysis, Pearson's correlation coefficient, Spearman's and Kendall’s rank correlation coefficients, linear and logistic regression analysis.
26
Narteh, Alexander Tetteh. "Correlation of Fluorescence Spectroscopy and Biochemical Oxygen Demand (BOD5) Using Regression Analysis." BYU ScholarsArchive, 2015. https://scholarsarchive.byu.edu/etd/5567.
Full textAbstract:
This research uses Regression analysis of fluorescence spectroscopy results to correlate with Biochemical Oxygen Demand (BOD5). Fluorescence spectroscopy was applied to samples taken from seven sample sites in the Provo and Orem waste water treatment plants found in Utah County. A total of 161 samples were collected for this research. 23 samples each were taken from four sites in the Provo waste water treatment plant namely Provo head works, aeration basin, primary filter settlement basin and the Provo effluent basin. The Orem head works, the clarifier and the Orem effluent basin were the three sample sites in the Orem waste water treatment plant where 23 samples each were collected to carry out the analysis. The fluorescent characteristics of the samples were determined using fluorescence spectrometry. These intensities were correlated with standard five day Biochemical Oxygen Demand (BOD5) values which were used as a measure of the amount of biodegradable organic material present. Chemical oxygen demand (COD) data were also taken from these treatment plants for correlation purposes. Three different correlation analyses were made which were the correlation of fluorescence spectroscopy excitation-emission matrix (EEM) against (1) individual sites BOD and COD values (2) Provo only and Orem only BOD and COD values (3) combined Provo and Orem BOD and COD values. The correlation of Individual site EEMs against BOD and COD values produced the best results. There was a higher correlation of EEM with BOD data than COD data. The R-squared for the combined Provo and Orem BOD data was 0.756 and that for COD was 0.729. Very high R-squared was obtained for Provo Influent data and Orem Influent data which were 0.955 and 0.946 respectively. This method can be used by wastewater stakeholders in deriving quick results in determining potential pollution events within a shorter time frame. This research demonstrates that there is a correlation between EEM and BOD/COD.
27
Daud, Isa Bin. "Influence diagnostics in regression with censored data." Thesis, Loughborough University, 1987. https://dspace.lboro.ac.uk/2134/11728.
Full textAbstract:
The work in this thesis is concerned with the development and extension of techniques for the assessment of influence diagnostics in data that include censored observations. Various regression models with censored data are presented and we concentrate on two models which are the accelerated failure time model, where the errors are generated by mixtures of normal distributions,and the Cox proportional hazards model. For the former, both finite discrete and continuous mixtures are considered, and an EM algorithm is used to determine measures of influence for each case. For the Cox proportional hazards model, various approaches to approximating influence curves are investigated. One-step or few-step approximations are developed using an EM algorithm and compared with a Newton-Raphson approach. Cook's measures of local influence are also investigated for the detection of influential cases in the data. The validity of the proportional hazards assumptions is also investigated. The residuals of Schoenfeld are examined for the possibility of being used to detect time dependence of the covariates in the proportional hazards model. Estimates to describe the nature of the time dependency computed from these residuals are presented.
28
Wang, Guoshen. "Analysis of Additive Risk Model with High Dimensional Covariates Using Correlation Principal Component Regression." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/math_theses/51.
Full textAbstract:
One problem of interest is to relate genes to survival outcomes of patients for the purpose of building regression models to predict future patients¡¯ survival based on their gene expression data. Applying semeparametric additive risk model of survival analysis, this thesis proposes a new approach to conduct the analysis of gene expression data with the focus on model¡¯s predictive ability. The method modifies the correlation principal component regression to handle the censoring problem of survival data. Also, we employ the time dependent AUC and RMSEP to assess how well the model predicts the survival time. Furthermore, the proposed method is able to identify significant genes which are related to the disease. Finally, this proposed approach is illustrated by simulation data set, the diffuse large B-cell lymphoma (DLBCL) data set, and breast cancer data set. The results show that the model fits both of the data sets very well.
29
Bremner, Alexandra P. "Localised splitting criteria for classification and regression trees." Thesis, Bremner, Alexandra P. (2004) Localised splitting criteria for classification and regression trees. PhD thesis, Murdoch University, 2004. https://researchrepository.murdoch.edu.au/id/eprint/440/.
Full textAbstract:
This thesis presents a modification of existing entropy-based splitting criteria for classification and regression trees. Trees are typically grown using splitting criteria that choose optimal splits without taking future splits into account. This thesis examines localised splitting criteria that are based on local averaging in regression trees or local proportions in classification trees. The use of a localised criterion is motivated by the fact that future splits result in leaves that contain local observations, and hence local deviances provide a better approximation of the deviance of the fully grown tree. While most recent research has focussed on tree-averaging techniques that are aimed at taking a moderately successful splitting criterion and improving its predictive power, this thesis concentrates on improving the splitting criterion.
Use of a localised splitting criterion captures local structures and enables later splits to capitalise on the placement of earlier splits when growing a tree. Using the localised splitting criterion results in much simpler trees for pure interaction data (data with no main effects) and can produce trees with fewer errors and lower residual mean deviances than those produced using a global splitting criterion when applied to real data sets with strong interaction effects.
The superiority of the localised splitting criterion can persist when multiple trees are grown and averaged using simple methods. Although a single tree grown using the localised splitting criterion can outperform tree averaging using the global criterion, generally improvements in predictive performance are achieved by utilising the localised splitting criterion's property of detecting local discontinuities and averaging over sets of trees grown by placing splits where the deviance is locally minimal. Predictive performance improves further when the degree of localisation of the splitting criterion is randomly selected and weighted randomisation is used with locally minimal deviances to produce sets of trees to average over. Although state of the art methods quickly average very large numbers of trees, thus making the performance of the splitting criterion less critical, predictive performance when the localised criterion is used in bagging indicates that different splitting methods warrant investigation.
The localised splitting criterion is most useful for growing one tree or a small number of trees to examine structure in the data. Structurally different trees can be obtained by simply splitting the data where the localised splitting criterion is locally optimal.
30
Bremner, Alexandra P. "Localised splitting criteria for classification and regression trees /." Access via Murdoch University Digital Theses Project, 2004. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20040606.142949.
Full text
31
Qin, Li-Xuan. "The clustering of regression models method with applications in gene expression data /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/9591.
Full text
32
Sakwe, Chantal Wase. "Analysis of Suspended Sediment Loads in Streams and Rivers using Linear Regression and Pearson Correlation." Youngstown State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1452867844.
Full text
33
Lee, Sungwook. "Semiparametric regression with random effects /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9842547.
Full text
34
Wang, Chenjie. "The design exploration method for adaptive design systems." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28084.
Full textAbstract:
Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Janet K. Allen; Committee Member: Benjamin Klein; Committee Member: Farrokh Mistree; Committee Member: Seung-Kyum Choi.
35
Guterstam, Rasmus, and Vidar Trojenborg. "Exploring a personal property pricing method in insurance context using multiple regression analysis." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254300.
Full textAbstract:
In general, insurance companies and especially their clients face long and complicated claims processes where payments rarely, and almost reluctantly, are made the same day. A part of this slow moving procedure is the fact that in some cases the insurer has to value the personal property themselves, which can be a tedious process. In conjunction with the insurance company Hedvig, this project address this issue by examining a pricing model for a specific personal property; smartphones - one of the most common occurring claim types in the insurance context. Using multiple linear regression with data provided by PriceRunner, 10 key characteristics out of 91 where found to have significant explanatory power in predicting the market price of a smartphone. The model successfully simulates this market price with an explained variance of 90%. Furthermore this thesis illustrates an intuitive example regarding pricing models for personal property of other sorts, identifying limiting key components to be data availability and product complexity.<br>I dagsläget står försäkringsbolag och deras kunder allt för ofta inför långa och komplicerade försäkringsärenden, där utbetalningar i regel aldrig sker samma dag. En del i denna långsamma och utdragna utbetalningsprocess är det faktum att försäkringsbolaget på egen hand måste uppskatta egendomens värde, vilket kan vara en mycket komplicerad process. I samarbete med försäkringsbolaget Hedvig undersöker denna rapport en värderingsmodell för ett av de vanligaste försäkringsärendena gällande personlig egendom, nämligen smartphones. Genom att använda multipel linjär regression med data försedd av PriceRunner har 10 av 91 nyckelfaktorer identifierats ha signifikant förklaringsgrad vid modellering av marknadsvärdet av en smartphone. Den framtagna modellen simulerar framgångsrikt marknadsvärdet med en 90-procentig förklaringsgrad av variansen. Vidare illustrerar denna rapport intuitiva riktlinjer för värderingsmodellering till andra typer av personlig egendom, samtidigt som den identifierar begränsande nyckelaspekter som exempelvis tillgången på data och egendomens inneboende komplexitet.
36
Chen, Zhe Haykin Simon S. "Stochastic approaches for correlation-based learning." *McMaster only, 2004.
Find full text
37
Dastmard, Benjamin. "A statistical analysis of the connection between test results and field claims for ECUs in vehicles." Thesis, KTH, Matematisk statistik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-118428.
Full textAbstract:
The objective of this thesis is to analyse theconnection between test results and field claims of ECUs (electronic controlunits) at Scania in order to improve the acceptance criteria and evaluatesoftware testing strategies. The connection is examined through computation ofdifferent measures of dependencies such as the Pearson’s correlation, Spearman’srank correlation and Kendall’s tau. The correlations are computed from testresults in different ECU projects and considered in a predictive model based onlogistic regression. Numerical results indicate a weak connection between testresults and field claims. This is partly due to insufficient number of ECUprojects and the lack of traceability of field claims and test results. Themain conclusion confirms the present software testing strategy. Continuoussoftware release and testing results in a lower field claim and thus a betterproduct.
38
Chen, Wei. "Analysis of Rheumatoid Arthritis Data using Logistic Regression and Penalized Approach." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5923.
Full textAbstract:
In this paper, a rheumatoid arthritis (RA) medicine clinical dataset with an ordinal response is selected to study this new medicine. In the dataset, there are four features, sex, age,treatment, and preliminary. Sex is a binary categorical variable with 1 indicates male, and 0 indicates female. Age is the numerical age of the patients. And treatment is a binary categorical variable with 1 indicates has RA, and 0 indicates does not have RA. And preliminary is a five class categorical variable indicates the patient’s RA severity status before taking the medication. The response Y is 5 class ordinal variable shows the severity of patient’s RA severity after taking the medication.
The primary aim of this study is to determine what factors play a significant role in determine the response after taking the medicine. First, cumulative logistic regression is applied to the dataset to examine the effect of various factors on ordinal response. Secondly, the ordinal response is categorized into two classes. Then logistic regression is conducted to the RA dataset to see if the variable selection would be different. Moreover, the shrinkage methods, elastic net and lasso are used to make a variable selection on the RA dataset of two-class response for the purpose of adding penalization to increase the model’s robustness.The four model results were compared at the end of the paper. From the comparison result, logistic regression has a better performance on variable selection than the other three approaches based on P-value.
39
Izadi, Hooshang. "Censored regression and the Pearson system of distributions : an estimation method and application to demand analysis." Thesis, University of Essex, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.252929.
Full text
40
Cai, Mingxuan. "BIVAS: a scalable Bayesian method for bi-level variable selection." HKBU Institutional Repository, 2018. https://repository.hkbu.edu.hk/etd_oa/482.
Full textAbstract:
In this thesis, we consider a Bayesian bi-level variable selection problem in high-dimensional regressions. In many practical situations, it is natural to assign group membership to each predictor. Examples include that genetic variants can be grouped at the gene level and a covariate from different tasks naturally forms a group. Thus, it is of interest to select important groups as well as important members from those groups. The existing methods based on Markov Chain Monte Carlo (MCMC) are often computationally intensive and not scalable to large data sets. To address this problem, we consider variational inference for bi-level variable selection (BIVAS). In contrast to the commonly used mean-field approximation, we propose a hierarchical factorization to approximate the posterior distribution, by utilizing the structure of bi-level variable selection. Moreover, we develop a computationally efficient and fully parallelizable algorithm based on this variational approximation. We further extend the developed method to model data sets from multi-task learning. The comprehensive numerical results from both simulation studies and real data analysis demonstrate the advantages of BIVAS for variable selection, parameter estimation and computational efficiency over existing methods. The BIVAS software with support of parallelization is implemented in R package `bivas' available at https://github.com/mxcai/bivas.
41
Webster, Gregg. "Bayesian logistic regression models for credit scoring." Thesis, Rhodes University, 2011. http://hdl.handle.net/10962/d1005538.
Full textAbstract:
The Bayesian approach to logistic regression modelling for credit scoring is useful when there are data quantity issues. Data quantity issues might occur when a bank is opening in a new location or there is change in the scoring procedure. Making use of prior information (available from the coefficients estimated on other data sets, or expert knowledge about the coefficients) a Bayesian approach is proposed to improve the credit scoring models. To achieve this, a data set is split into two sets, “old” data and “new” data. Priors are obtained from a model fitted on the “old” data. This model is assumed to be a scoring model used by a financial institution in the current location. The financial institution is then assumed to expand into a new economic location where there is limited data. The priors from the model on the “old” data are then combined in a Bayesian model with the “new” data to obtain a model which represents all the available information. The predictive performance of this Bayesian model is compared to a model which does not make use of any prior information. It is found that the use of relevant prior information improves the predictive performance when the size of the “new” data is small. As the size of the “new” data increases, the importance of including prior information decreases
42
Spaulding, Aleigha, Jessica R. Barbee, Nathan L. Hale, et al. "Analysis of Birth Rate and Predictors Using Linear Regression Model and Propensity Score Matching Method." Digital Commons @ East Tennessee State University, 2019. https://dc.etsu.edu/asrf/2019/schedule/35.
Full textAbstract:
Evaluating the effectiveness of an intervention can pose challenges if there is not an adequate control group. The effects of the intervention can be distorted by observable differences in the characteristics of the control and treatment groups. Propensity score matching can be used to confirm the outcomes of an intervention are due to the treatment and not other characteristics that may also explain the intervention effects. Propensity score matching is an advanced statistical technique that uses background information on the characteristics of the study population to establish matched pairs of treated participants and controls. This technique improves the quality of control groups and allowing for a better evaluation of the true effects of an intervention. The purpose of this study was to implement this technique to derive county-level matches across the southeastern United States for existing counties within a single state where future statewide initiatives are planned. Statistical analysis was performed using SAS 9.4 (Cary, NC, USA). A select set of key county-level socio-demographic measures theoretically relevant for deriving appropriate matches was examined. These include the proportion of African Americans in population, population density, and proportion of the female population below poverty level. To derive the propensity-matched counties, a logistic regression model with the state of primary interest as the outcome was conducted. The baseline covariates of interest were included in the model and used to predict the probability of a county being in the state of primary interest; this acts as the propensity score used to derive matched controls. A caliper of 0.2 was used to ensure the ratio of the variance of the linear propensity score in the control group to the variance of the linear propensity score in the treatment group is close to 1. The balance of covariates before and after the propensity score matching were assessed to determine if significant differences in each respective covariate persisted after the propensity score matching. Before matching, a significant difference was found in the proportion of African Americans in control group (21.08%, n=3,450) and treatment group (36.95%, n=230) using the t-test (P<0.0001). The percent of females below poverty level showed significant difference between control and treatment group (P=0.0264). The t-test of population density also showed significant differences between the groups (P=0.0424). After matching, the mean differences for the treated-control groups were all zero for these three covariates and the characteristics were no longer showing any significant differences between the two groups. This study found that the use of propensity score matching methods improved the accuracy of matched controls. Ensuring that the control and treatment counties have statistically similar characteristics is important for improving the rigor of future studies examining county-level outcomes. Propensity score matching does not account for unobserved differences between the treatment and control groups that may affect the observed outcomes; however, it does ensure that the observable characteristics between the groups are statistically similar.This method reduces the threat to internal validity that observable characteristics pose on interventions by matching for these potentially confounding characteristics.
43
Kalousková, Petra. "Posouzení finanční výkonnosti společnosti pomocí analýzy časových řad." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2018. http://www.nusl.cz/ntk/nusl-377934.
Full textAbstract:
The diploma thesis deals with an assessment of the topical financial situation of BARVY A LAKY TELURIA, s. r. o. using the time series analysis. The theoretical part focuses on the description of the financial indicators, analysis of the time series, and subsequently the regressive and correlative analysis. In the practical part, selected financial indicators are statistically analyzed. The future two-year development of indicators is predicted on the basis of the selected models; subsequently dependencies among the particular indicators are determined. In the conclusion, proposals to ameliorate the current financial situation of the company are recommended, which was carried out on the basis of the identified shortcomings.
44
Funa, Laura. "Customer Satisfaction Analysis." Thesis, Linköpings universitet, Statistik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-71707.
Full textAbstract:
The objective of this master thesis is to identify “key-drivers” embedded in customer satisfaction data. The data was collected by a large transportation sector corporation during five years and in four different countries. The questionnaire involved several different sections of questions and ranged from demographical information to satisfaction attributes with the vehicle, dealer and several problem areas. Various regression, correlation and cooperative game theory approaches were used to identify the key satisfiers and dissatisfiers. The theoretical and practical advantages of using the Shapley value, Canonical Correlation Analysis and Hierarchical Logistic Regression has been demonstrated and applied to market research.
45
Ma, Miaomiao [Verfasser]. "Correlation Dimension analysis of complex hydrological systems : what information can the method provide? / Miaomiao Ma." Berlin : Freie Universität Berlin, 2013. http://d-nb.info/103687284X/34.
Full text
46
Vrugtman, Rosanne. "Dimensions of Intuition first-round validation studies /." Diss., St. Louis, Mo. : University of Missouri--St. Louis, 2009. http://etd.umsl.edu/r3801.
Full text
47
Cullen, Kathleen Ann. "Forecasting electricity demand using regression and Monte Carlo simulation under conditions of insufficient data." Morgantown, W. Va. : [West Virginia University Libraries], 1999. http://etd.wvu.edu/templates/showETD.cfm?recnum=903.
Full textAbstract:
Thesis (M.S.)--West Virginia University, 1999.<br>Title from document title page. Document formatted into pages; contains x, 137 p. : ill., map Vita. Includes abstract. Includes bibliographical references (p. 99-107).
48
Miller, Carlton W. "Optimization of model analysis and cross-orthogonality techniques to insure finite element model correlation to test data /." Online version of thesis, 1993. http://hdl.handle.net/1850/12216.
Full text
49
Prudencio, Gerald, Diego Pino, Luis Arauzo, and Carlos Raymundo. "Productivity analysis of LHD equipment using the multiple linear regression method in an underground mine in Peru." International Institute of Informatics and Systemics, IIIS, 2019. http://hdl.handle.net/10757/656294.
Full textAbstract:
El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.<br>The current study is based on a multiple linear regression analysis with an objective to formulate an equation related to the productivity analysis of LHD equipment using independent variables such as the effective utilization of the equipment. To identify the independent variables, main productive factors, such as the actual capacity of the buckets, the transport cycles in the cleaning process, and the performance by means of curves, were analyzed. Comparisons of a Peruvian underground mine case study exhibited that the battery-powered equipment denoted similar production efficiencies to that exhibited by its diesel counterparts; however, the three-tier approach observed that the battery-powered equipment could achieve production efficiencies that are up to 13.8% more as compared to that achieved using its diesel counterparts because of increased effective utilization that can be attributed to long MTBF. The results of this study exhibit that LHDs under battery-powered storage are feasible for underground mining not only because of the fact that they do not emit any polluting gases, which helps to mitigate pollution, but also because of their good production performance that can be considered to be an important pillar in deep mining. Copyright 2019.
50
Li, Ji. "Cox Model Analysis with the Dependently Left Truncated Data." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/math_theses/88.
Full textAbstract:
A truncated sample consists of realizations of a pair of random variables (L, T) subject to the constraint that L ≤T. The major study interest with a truncated sample is to find the marginal distributions of L and T. Many studies have been done with the assumption that L and T are independent. We introduce a new way to specify a Cox model for a truncated sample, assuming that the truncation time is a predictor of T, and this causes the dependence between L and T. We develop an algorithm to obtain the adjusted risk sets and use the Kaplan-Meier estimator to estimate the Marginal distribution of L. We further extend our method to more practical situation, in which the Cox model includes other covariates associated with T. Simulation studies have been conducted to investigate the performances of the Cox model and the new estimators.