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(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 ...

(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 ...

(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 ...

(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 ...

(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 ...

(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 ...

(1992)As computer experiments are widely used in engineering and various other fields of science and technology, stochastic modeling and statistical analysis have been introduced to handle their outputs. Since in certain computer ...

(20120918)The state space model has been widely used in various fields including economics, finance, bioinformatics, oceanography, and tomography. The goal of the filtering problem is to find the posterior distribution of the hidden ...

(1995)The ordinary least squares (OLS) method is known to be efficient for linear models when the errors are homogeneous with Gaussian distributions, but troublesome with heteroscedastic or nonGaussian errors. For the latter ...

(20120627)Tissue classification and feature selection have been increasing studied during the last two decades, however the available methods are still limited and need improvement. In this manuscript, we develop tissue classification ...

(1990)Dimension reduction techniques are important in the problem of regression and prediction when the nominal number of predicting variables is greater than the number of observations. Two methods, principal components analysis ...

(1989)A statistical procedure is developed with the purpose of detecting internal bias occurring concurrently in several items in an ability test. Concurrent internal bias (CIB) is considered in a nonparametric multidimensional ...

(20110825)Longitudinal data arise frequently in many studies where measurements are obtained from a subject repeatedly over time. Consequently, measurements within a subject are correlated. We address two rather important but ...

(20130822)Highdimensional correlated data arise frequently in many studies. My primary research interests lie broadly in statistical methodology for correlated data such as longitudinal data and panel data. In this thesis, we address ...

(1995)Unidimensionality is one of the most important assumptions required by much of the currently used item response theory (IRT) methodologies. In the first part of this thesis, a further and nontrivial practical refinement ...

(1994)A new index based on the conditional covariance of item scores given a latent variable is defined and investigated to assess dimensionality in educational and psychological test data. This index successfully detects the ...

(1995)Randles' one sample multivariate sign test based on interdirections is extended to two sample and multisample tests. A heuristic argument suggests that when samples are drawn from elliptically symmetric distributions all ...

(201212)Traditional linear mixed effect models assume the distributions of the random effects and errors follow normal distribution with mean zero and homoscedastic variance sigma square. This thesis presents a new nonparametric ...

(1990)Let $\{$(X$\sb{\rm t}$,Y$\sb{\rm t}$): t $\in$ N$\}$ be a strictly stationary process with X$\sb{\rm t}$ being R$\sp{\rm d}$valued and Y$\sb{\rm t}$ being real valued. Consider the problem of estimating the conditional ...

(1995)The thesis consists of six chapters and focus on two topics: quantile regression and survival analysis. Firstly, direct use of regression quantiles to construct confidence intervals and confidence bands for conditional ...
Now showing items 928 of 52