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Dissertations / Theses on the topic 'Distributional regression'

Author: Grafiati

Published: 11 December 2022

Last updated: 31 July 2025

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1

Kasturiratna, Dhanuja. "Assessing the Distributional Assumptions in One-Way Regression Model." Bowling Green State University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1148479945.

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2

Hirvela, Kyle Ray. "Park Access and Distributional Inequities in Pinellas County, Florida." Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3150.

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Although environmental justice research has traditionally focused on environmental disamenities and health hazards, recent studies have begun to examine social inequities in the distribution of urban amenities such as street trees and parks that provide several direct and indirect health benefits to local residents. This thesis adds to this knowledge by evaluating distributional inequities in both distribution and access to parks in Pinellas County, the most densely populated and one of the most racially segregated counties in Florida. An important objective was to determine if neighborhoods w

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3

Pihl, Svante, and Leonardo Olivetti. "An Empirical Comparison of Static Count Panel Data Models: the Case of Vehicle Fires in Stockholm County." Thesis, Uppsala universitet, Statistiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-412014.

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In this paper we study the occurrences of outdoor vehicle fires recorded by the Swedish Civil Contingencies Agency (MSB) for the period 1998-2019, and build static panel data models to predict future occurrences of fire in Stockholm County. Through comparing the performance of different models, we look at the effect of different distributional assumptions for the dependent variable on predictive performance. Our study concludes that treating the dependent variable as continuous does not hamper performance, with the exception of models meant to predict more uncommon occurrences of fire. Further

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4

Afrifa-Yamoah, Ebenezer. "Imputation, modelling and optimal sampling design for digital camera data in recreational fisheries monitoring." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2021. https://ro.ecu.edu.au/theses/2387.

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Digital camera monitoring has evolved as an active application-oriented scheme to help address questions in areas such as fisheries, ecology, computer vision, artificial intelligence, and criminology. In recreational fisheries research, digital camera monitoring has become a viable option for probability-based survey methods, and is also used for corroborative and validation purposes. In comparison to onsite surveys (e.g. boat ramp surveys), digital cameras provide a cost-effective method of monitoring boating activity and fishing effort, including night-time fishing activities. However, there

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5

Pic, Romain. "Statistical postprocessing of ensemble forecasts : theory, application in weather forecasting and verification." Electronic Thesis or Diss., Bourgogne Franche-Comté, 2024. http://www.theses.fr/2024UBFCD018.

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Cette thèse porte sur l'utilisation de méthodes de post-traitement statistiques dans le but d'améliorer les prévisions d'ensemble. Les prévisions d'ensemble sont des prévisions composées de différents membres dont la diversité tente de capturer l'incertitude liée à la prédiction. Les prévisions d'ensemble souffrent de biais et de sous-dispersion et un post-traitement est donc nécessaire afin d'améliorer leur performance. D'un point de vue théorique, cette thèse apporte des résultats sur le taux de convergence en régression distributionnelle en termes de continuous ranked probability score. De

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6

Lai, Pik-ying, and 黎碧瑩. "Lp regression under general error distributions." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30287844.

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7

Chen, Xinyu. "Inference in Constrained Linear Regression." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-theses/405.

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Regression analyses constitutes an important part of the statistical inference and has great applications in many areas. In some applications, we strongly believe that the regression function changes monotonically with some or all of the predictor variables in a region of interest. Deriving analyses under such constraints will be an enormous task. In this work, the restricted prediction interval for the mean of the regression function is constructed when two predictors are present. I use a modified likelihood ratio test (LRT) to construct prediction intervals.

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8

Wei, Yan. "Robust mixture regression models using t-distribution." Kansas State University, 2012. http://hdl.handle.net/2097/14110.

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Master of Science<br>Department of Statistics<br>Weixin Yao<br>In this report, we propose a robust mixture of regression based on t-distribution by extending the mixture of t-distributions proposed by Peel and McLachlan (2000) to the regression setting. This new mixture of regression model is robust to outliers in y direction but not robust to the outliers with high leverage points. In order to combat this, we also propose a modified version of the proposed method, which fits the mixture of regression based on t-distribution to the data after adaptively trimming the high leverage points. We

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9

Parker, I. "Transformation in regression, estimation, testing and modelling." Thesis, University of St Andrews, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.384598.

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10

Chang, Kai-Ming. "Bayesian regression and discrimination with many variables." Thesis, University College London (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268337.

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11

Cao, Chendi. "Linear regression with Laplace measurement error." Kansas State University, 2016. http://hdl.handle.net/2097/32719.

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Master of Science<br>Statistics<br>Weixing Song<br>In this report, an improved estimation procedure for the regression parameter in simple linear regression models with the Laplace measurement error is proposed. The estimation procedure is made feasible by a Tweedie type equality established for E(X|Z), where Z = X + U, X and U are independent, and U follows a Laplace distribution. When the density function of X is unknown, a kernel estimator for E(X|Z) is constructed in the estimation procedure. A leave-one-out cross validation bandwidth selection method is designed. The finite sample perform

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12

Xing, Yanru. "Robust mixture regression model fitting by Laplace distribution." Kansas State University, 2013. http://hdl.handle.net/2097/16534.

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Master of Science<br>Department of Statistics<br>Weixing Song<br>A robust estimation procedure for mixture linear regression models is proposed in this report by assuming the error terms follow a Laplace distribution. EM algorithm is imple- mented to conduct the estimation procedure of missing information based on the fact that the Laplace distribution is a scale mixture of normal and a latent distribution. Finite sample performance of the proposed algorithm is evaluated by some extensive simulation studies, together with the comparisons made with other existing procedures in this literat

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13

Kim, Sungsu. "Inverse circular regression with possibly asymmetric error distribution." Diss., UC access only, 2009. http://proquest.umi.com/pqdweb?index=90&did=1887560071&SrchMode=1&sid=1&Fmt=7&retrieveGroup=0&VType=PQD&VInst=PROD&RQT=309&VName=PQD&TS=1270249121&clientId=48051.

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Thesis (Ph. D.)--University of California, Riverside, 2009.<br>Includes abstract. Includes bibliographical references (leaves 107-109). Issued in print and online. Available via ProQuest Digital Dissertations.

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14

Liu, Xi. "Some new developments for quantile regression." Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/16204.

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Quantile regression (QR) (Koenker and Bassett, 1978), as a comprehensive extension to standard mean regression, has been steadily promoted from both theoretical and applied aspects. Bayesian quantile regression (BQR), which deals with unknown parameter estimation and model uncertainty, is a newly proposed tool of QR. This thesis aims to make some novel contributions to the following three issues related to QR. First, whereas QR for continuous responses has received much attention in literatures, QR for discrete responses has received far less attention. Second, conventional QR methods often sh

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15

van, de Ven Remy Julius. "Estimation in mixed Poisson regression models." Thesis, The University of Sydney, 1996. https://hdl.handle.net/2123/26822.

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This thesis considers estimation of the parameters associated with models for count data displaying over-dispersion relative to the Poisson distribution where the over-dispersion is modelled using mixing. It is divided into seven chapters with Chapters Two to Five specific to the over-dispersed Poisson problem whilst Chapter Seven, which uses results from Chapter Six, is more general. The motivation for some of this work was the modelling of repeat counts of the number of fibres contained on microscopic slides as obtained by asbestos fibre counters and the subsequent estimation of mean fibre c

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16

Lee, Sungwook. "Semiparametric regression with random effects /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9842547.

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17

Taylor, James William. "Predictive distributions, quantile regression and the combination of forecasts." Thesis, London Business School (University of London), 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338470.

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18

Paz, Rosineide Fernando da. "Alternative regression models to beta distribution under bayesian approach." Universidade Federal de São Carlos, 2017. https://repositorio.ufscar.br/handle/ufscar/9146.

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Submitted by Aelson Maciera (aelsoncm@terra.com.br) on 2017-09-27T18:09:58Z No. of bitstreams: 1 TeseRFP.pdf: 2142415 bytes, checksum: 8dcd8615da0b442e9f1b52f35364715b (MD5)<br>Approved for entry into archive by Ronildo Prado (producaointelectual.bco@ufscar.br) on 2017-10-10T18:16:14Z (GMT) No. of bitstreams: 1 TeseRFP.pdf: 2142415 bytes, checksum: 8dcd8615da0b442e9f1b52f35364715b (MD5)<br>Approved for entry into archive by Ronildo Prado (producaointelectual.bco@ufscar.br) on 2017-10-10T18:16:22Z (GMT) No. of bitstreams: 1 TeseRFP.pdf: 2142415 bytes, checksum: 8dcd8615da0b442e9f1b52f353647

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19

Åkesson, Mattias. "Learning Phantom Dose Distribution using Regression Artificial Neural Networks." Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-380767.

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Before a radiation treatment on a cancer patient can get accomplished the treatment planning system (TPS) needs to undergo a quality assurance (QA). The QA consists of a pre-treatment (PT-QA) on a synthetic phantom body. During the PT-QA, data is collected from the phantom detectors, a set of monitors (transmission detectors) and the angular state of the machine. The outcome of this thesis project is to investigate if it is possible to predict the radiation dose distribution on the phantom body based on the data from the transmission detectors and the angular state of the machine. The motive f

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20

Liu, Yantong. "Robust mixture linear EIV regression models by t-distribution." Kansas State University, 2012. http://hdl.handle.net/2097/15157.

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Master of Science<br>Department of Statistics<br>Weixing Song<br>A robust estimation procedure for mixture errors-in-variables linear regression models is proposed in the report by assuming the error terms follow a t-distribution. The estimation procedure is implemented by an EM algorithm based on the fact that the t-distribution is a scale mixture of normal distribution and a Gamma distribution. Finite sample performance of the proposed algorithm is evaluated by some extensive simulation studies. Comparison is also made with the MLE procedure under normality assumption.

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21

Zhang, Jingyi. "Robust mixture regression modeling with Pearson type VII distribution." Kansas State University, 2013. http://hdl.handle.net/2097/15648.

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Master of Science<br>Department of Statistics<br>Weixing Song<br>A robust estimation procedure for parametric regression models is proposed in the paper by assuming the error terms follow a Pearson type VII distribution. The estimation procedure is implemented by an EM algorithm based on the fact that the Pearson type VII distributions are a scale mixture of a normal distribution and a Gamma distribution. A trimmed version of proposed procedure is also discussed in this paper, which can successfully trim the high leverage points away from the data. Finite sample performance of the proposed alg

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22

Noufaily, Angela. "Parametric quantile regression based on the generalised gamma distribution." Thesis, Open University, 2011. http://oro.open.ac.uk/54496/.

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Quantile regression offers an extension to regression analysis where a modified version of the least squares method allows the fitting of quantiles at every percentile of the data rather than the mean only. Using the well-known three-parameter generalised gamma distribution to model variation in data, we present a parametric quantile regression study for positive univariate reference charts. The study constitutes an overall package that includes all different stages of parametric modeling starting from model identification to parameter estimation, model selection and finally model checking. We

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23

Li, Xiongya. "Robust multivariate mixture regression models." Diss., Kansas State University, 2017. http://hdl.handle.net/2097/38427.

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Doctor of Philosophy<br>Department of Statistics<br>Weixing Song<br>In this dissertation, we proposed a new robust estimation procedure for two multivariate mixture regression models and applied this novel method to functional mapping of dynamic traits. In the first part, a robust estimation procedure for the mixture of classical multivariate linear regression models is discussed by assuming that the error terms follow a multivariate Laplace distribution. An EM algorithm is developed based on the fact that the multivariate Laplace distribution is a scale mixture of the multivariate standard no

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24

Kong, Fanhui. "Asymptotic distributions of Buckley-James estimator." Online access via UMI:, 2005.

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25

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 grad

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26

Peiris, Thelge Buddika. "Constrained Statistical Inference in Regression." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/dissertations/934.

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Regression analysis constitutes a large portion of the statistical repertoire in applications. In case where such analysis is used for exploratory purposes with no previous knowledge of the structure one would not wish to impose any constraints on the problem. But in many applications we are interested in a simple parametric model to describe the structure of a system with some prior knowledge of the structure. An important example of this occurs when the experimenter has the strong belief that the regression function changes monotonically in some or all of the predictor variables in a region

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27

Ewertzh, Jacob. "Bankruptcy Distributions and Modelling for Swedish Companies Using Logistic Regression." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252329.

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This thesis discusses the concept of bankruptcy, or default, for Swedish companies. The actual distribution over time is considered both on aggregate level and within different industries. Several models are constructed to best possible describe the default frequency. Mainly logistic regression models are designed for this purpose, but various other models are considered. Some of these are constructed for comparison and for the ambition to produce the most accurate model possible. A large data set of nearly 30 million quarterly observations is used in the analysis. Taking into account micro an

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Bai, Xiuqin. "Robust mixtures of regression models." Diss., Kansas State University, 2014. http://hdl.handle.net/2097/18683.

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Doctor of Philosophy<br>Department of Statistics<br>Kun Chen and Weixin Yao<br>This proposal contains two projects that are related to robust mixture models. In the robust project, we propose a new robust mixture of regression models (Bai et al., 2012). The existing methods for tting mixture regression models assume a normal distribution for error and then estimate the regression param- eters by the maximum likelihood estimate (MLE). In this project, we demonstrate that the MLE, like the least squares estimate, is sensitive to outliers and heavy-tailed error distributions. We propose a r

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Ratnasingam, Suthakaran. "Sequential Change-point Detection in Linear Regression and Linear Quantile Regression Models Under High Dimensionality." Bowling Green State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu159050606401363.

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30

Al-Hamzawi, Rahim Jabbar Thaher. "Prior elicitation and variable selection for bayesian quantile regression." Thesis, Brunel University, 2013. http://bura.brunel.ac.uk/handle/2438/7501.

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Bayesian subset selection suffers from three important difficulties: assigning priors over model space, assigning priors to all components of the regression coefficients vector given a specific model and Bayesian computational efficiency (Chen et al., 1999). These difficulties become more challenging in Bayesian quantile regression framework when one is interested in assigning priors that depend on different quantile levels. The objective of Bayesian quantile regression (BQR), which is a newly proposed tool, is to deal with unknown parameters and model uncertainty in quantile regression (QR).

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Wan, Kam-ming Galaxy. "Application of logistic regression to female labor force participation in Hong Kong." [Hong Kong : University of Hong Kong], 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13781467.

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32

Heise, Mark A. "Optimal designs for a bivariate logistic regression model." Diss., Virginia Tech, 1993. http://hdl.handle.net/10919/38538.

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In drug-testing experiments the primary responses of interest are efficacy and toxicity. These can be modeled as a bivariate quantal response using the Gumbel model for bivariate logistic regression. D-optimal and Q-optimal experimental designs are developed for this model The Q-optimal design minimizes the average asymptotic prediction variance of p(l,O;d), the probability of efficacy without toxicity at dose d, over a desired range of doses. In addition, a new optimality criterion, T -optimality, is developed which minimizes the asymptotic variance of the estimate of the therapeutic index.

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33

Dong, Fanglong. "Bayesian Model Checking in Multivariate Discrete Regression Problems." Bowling Green State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1223329230.

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34

Sazak, Hakan Savas. "Estimation And Hypothesis Testing In Stochastic Regression." Phd thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/3/724294/index.pdf.

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Regression analysis is very popular among researchers in various fields but almost all the researchers use the classical methods which assume that X is nonstochastic and the error is normally distributed. However, in real life problems, X is generally stochastic and error can be nonnormal. Maximum likelihood (ML) estimation technique which is known to have optimal features, is very problematic in situations when the distribution of X (marginal part) or error (conditional part) is nonnormal. Modified maximum likelihood (MML) technique which is asymptotically giving the estimators equivalent to

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35

Tao, Jinxin. "Comparison Between Confidence Intervals of Multiple Linear Regression Model with or without Constraints." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-theses/404.

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Regression analysis is one of the most applied statistical techniques. The sta- tistical inference of a linear regression model with a monotone constraint had been discussed in early analysis. A natural question arises when it comes to the difference between the cases of with and without the constraint. Although the comparison be- tween confidence intervals of linear regression models with and without restriction for one predictor variable had been considered, this discussion for multiple regres- sion is required. In this thesis, I discuss the comparison of the confidence intervals between a

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36

Aristodemou, Katerina. "New regression methods for measures of central tendency." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/9268.

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Measures of central tendency have been widely used for summarising statistical data, with the mean being the most popular summary statistic. However, in reallife applications it is not always the most representative measure of central location, especially when dealing with data which is skewed or contains outliers. Alternative statistics with less bias are the median and the mode. Median and quantile regression has been used in different fields to examine the effect of factors at different points of the distribution. Mode estimation, on the other hand, has found many applications in cases wher

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Hudson, Richard James Frederick. "Long memory spectral regression : an approach using generalised least squares." Thesis, Queensland University of Technology, 2002.

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Kim, Hyun-Joo. "Model selection criteria based on Kullback information measures for Weibull, logistic, and nonlinear regression frameworks /." free to MU campus, to others for purchase, 2000. http://wwwlib.umi.com/cr/mo/fullcit?p9988677.

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Farias, Rafael Braz Azevedo. "Modelos multivariados binários com funções de ligação assimétricas." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-15082012-233258/.

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Conjuntos de dados com respostas multivariadas aparecem frequentemente em pesquisas em que os dados são provenientes de questionários. Exemplos mais comuns são pesquisas de opinião, mais especificamente, pesquisas de marketing em que a preferência do consumidor em potencial é avaliado: pelo produto, marca, preço, praça, promoção e etc. Um tipo pesquisa de opinião que ganha grande destaque no Brasil de dois em dois anos são as pesquisas eleitorais de intenção de votos. Nós introduzimos nesta tese uma classe de modelos de regressão multivariados com funções de ligação assimétricas para o ajus

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Zhang, Ling. "Efficiency Comparison of Distribution-Free Transformations in the Straight-Line Regression Problem." Thesis, Uppsala University, Department of Statistics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-126667.

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<p>In statistical inference of the distribution-free straight-line regression problem, two common transformations, rank transformation and sign transformation, are used to construct the test statistics. When shall we need to use the transformations and which transformation is more efficient are two common questions met by researchers. In this thesis, we will discuss the comparison of the efficiencies of the statistics before and after the rank transformation or the sign transformation in both theoretical and practical ways. Simulation is also used to compare the efficiencies of the statistics

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Ho, Linda Lee. "Análise de contagens multivariadas." Universidade de São Paulo, 1995. http://www.teses.usp.br/teses/disponiveis/3/3136/tde-04072017-101027/.

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Este trabalho apresenta uma análise estatística de contagens multivariadas proveniente de várias populações através de modelos de regressão. Foram considerados casos onde os vetores respostas obedeçam às distribuições Poisson multivariada e Poisson log-normal multivariada. Esta distribuição admite correlação de ambos sinais entre componentes do vetor resposta, enquanto que as distribuições mais usuais para dados de contagens (como a Poisson multivariada) admitem apenas correlação positiva entre as componentes do vetor resposta. São discutidos métodos de estimação e testes de hipóteses sobre os

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Ribom, Henrik, and Mathias Sjöberg. "Intraday Analysis & Prediction of Volume Distribution on the Stockholm Stock Exchange : An exploratory study of volume distribution and automated trading." Thesis, KTH, Matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-170148.

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The purpose of this study is to create a model of prediction for the volume distribution. Due to the lack of previous studies on the subject, an exploratory approach is used, with the purpose of serving as a proof of concept for further research. By looking at all market data from the Stockholm stock exchange the volume distribution of individual order books are matched with a mixed beta distribution and scaled by a prediction based on a linear regression. The model provided in this study outperforms the floating mean by quite a good margin. Some days are, almost by definition, impossible to g

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Wan, Kam-ming Galaxy, and 尹錦銘. "Application of logistic regression to female labor force participationin Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31977522.

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Silva, Pedro Luis do Nascimento. "Utilizing auxiliary information in sample survey estimation and analysis." Thesis, University of Southampton, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.300492.

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Nakamura, Luiz Ricardo. "Advances on the Birnbaum-Saunders distribution." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-30092016-171320/.

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The Birnbaum-Saunders (BS) distribution is the most popular model used to describe lifetime process under fatigue. Throughout the years, this distribution has received a wide ranging of applications, demanding some more flexible extensions to solve more complex problems. One of the most well-known extensions of the BS distribution is the generalized Birnbaum- Saunders (GBS) family of distributions that includes the Birnbaum-Saunders special-case (BSSC) and the Birnbaum-Saunders generalized t (BSGT) models as special cases. Although the BS-SC distribution was previously developed in the literat

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Pupashenko, Daria [Verfasser], and Peter [Akademischer Betreuer] Ruckdeschel. "Robustness for regression models with asymmetric error distribution / Daria Pupashenko. Betreuer: Peter Ruckdeschel." Kaiserslautern : Technische Universität Kaiserslautern, 2015. http://d-nb.info/1069938793/34.

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Sánchez, Rocio Paola Maehara. "An extension of Birnbaum-Saunders distributions based on scale mixtures of skew-normal distributions with applications to regression models." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-14052018-202935/.

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The aim of this work is to present an inference and diagnostic study of an extension of the lifetime distribution family proposed by Birnbaum and Saunders (1969a,b). This extension is obtained by considering a skew-elliptical distribution instead of the normal distribution. Specifically, in this work we develop a Birnbaum-Saunders (BS) distribution type based on scale mixtures of skew-normal distributions (SMSN). The resulting family of lifetime distributions represents a robust extension of the usual BS distribution. Based on this family, we reproduce the usual properties of the BS distribut

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48

Guan, Tianyuan. "Sample Size Calculations in Simple Linear Regression: A New Approach." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627667392849137.

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Wan, Chung-him, and 溫仲謙. "Analysis of zero-inflated count data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43703719.

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Wan, Chung-him. "Analysis of zero-inflated count data." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B43703719.

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