 IDEALS Home
 →
 College of Liberal Arts and Sciences
 →
 Dept. of Statistics
 →
 Dissertations and Theses  Statistics
 →
 Browse Dissertations and Theses  Statistics by Title
Browse Dissertations and Theses  Statistics by Title
Now showing items 827 of 135

(1989)Many authors, for example, Fisher (1950), Pearson (1938), Birnbaum (1954), Good (1955), Littell and Folks (1971, 1973), Berk and Cohen (1979), and Koziol, Perlman, and Rasmussen (1988), have studied the problem of combining ...
application/pdf
PDF (7MB) 
(20120201)Bayesian inference provides a flexible way of combiningg data with prior information. However, quantile regression is not equipped with a parametric likelihood, and therefore, Bayesian inference for quantile regression ...
application/pdf
PDF (446kB) 
(2002)This thesis presents a progression from theory development to realdata application. Chapter 1 gives a literature review of other psychometric models for formative assessment, or cognitive diagnosis models, as an introduction ...
application/pdf
PDF (9MB) 
(1993)We consider the problem of regressing a dichotomous response variable on a predictor variable. Our interest is in modelling the probability of occurrence of the response as a function of the predictor variable, and in ...
application/pdf
PDF (6MB) 
(20110525)The latent class model (LCM) is a statistical method that introduces a set of latent categorical variables. The main advantage of LCM is that conditional on latent variables, the manifest variables are mutually independent ...
application/pdf
PDF (5MB) 
(20110525)Quantile regression, as a supplement to the mean regression, is often used when a comprehensive relationship between the response variable and the explanatory variables is desired. The traditional frequentists’ approach ...
application/pdf
PDF (374kB) 
(2007)Clustering and classification have been important tools to address a broad range of problems in fields such as image analysis, genomics, and many other areas. Basically, these clustering problems can be simplified as two ...
application/pdf
PDF (2MB) 
(2000)To effectively build a regression model with a large number of covariates is no easy task. We consider using dimension reduction before building a parametric or spline model. The dimension reduction procedure is based on ...
application/pdf
PDF (4MB) 
(2000)Motivated by consulting in infrastructure studies, we consider the estimation and inference for regression models where the response variable is bounded or censored. In these conditions, least squares methods are not ...
application/pdf
PDF (3MB) 
(2006)The classical approaches to clustering are hierarchical and kmeans. They are popular in practice. However, they can not address the issue of determining the number of clusters within the data. In this dissertation, we ...
application/pdf
PDF (2MB) 
(1991)Consider the model $y\sb{lj} = \mu\sb{l}(t\sb{j})$ + $\varepsilon\sb{lj}$, $l = 1,..,m$ and $j = 1,..,n,$ where $\varepsilon\sb{lj}$ are independent mean zero finite variance random variables. Under the above setting we ...
application/pdf
PDF (5MB) 
(1990)Twostage Bayes procedures, also known as Bayes double sample procedures, for estimating the mean of exponential family distributions are given by Cohen and Sackrowitz (1984). In their study, they develop double sample ...
application/pdf
PDF (2MB) 
(2004)The flexible forms of nonparametric IRT models make test equating more challenging. Though linear equating under parametric IRT models is obvious and appropriate, it might not be appropriate for nonparametric models. Two ...
application/pdf
PDF (3MB) 
(20170630)Over the last two decades, we have witnessed a massive explosion of our data collection abilities and the birth of a "big data" age. This has led to an enormous interest in statistical inference of a new type of complex ...
application/pdf
PDF (14MB) 
(1996)Statistical classification and calibration with highdimensional data are studied. We have proposed new classification and calibration procedures for highdimensional data and have established dimensional consistency for ...
application/pdf
PDF (4MB) 
(2000)In the logistic item response theory models, the number of parameters tends to infinity together with the sample size. Thus, there has been a longstanding question of whether the joint maximum likelihood estimates for these ...
application/pdf
PDF (3MB) 
(20120627)For my thesis, I have worked on two projects: modeling parasite dynamics (Chapter 2) and complementary dimensionality analysis (Chapter 3). In the first project, we study a longitudinal data of infection with the parasite ...
application/pdf
PDF (2MB) 
(2009)Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, ...
application/pdf
PDF (1MB) 
(1989)The theory of statistical breakdown is studied from two different angles. Firstly, the finite sample breakdown points of estimators are found to be inherently related to their tail performances. This connection provides ...
application/pdf
PDF (3MB) 
(1990)Probability density functions are estimated by the method of maximum likelihood in sequences of regular exponential families. The approximation families of logdensities that we consider are polynomials, splines, and ...
application/pdf
PDF (3MB)
Now showing items 827 of 135