Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 17 of 17 for “"Normal model"”.
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Network Reliability Analysis under the Multivariate Normal Model
… be correlated. In this thesis we develop a novel model for probabilistic link failures that captures the correlation expected in HF communication networks. We focus on two problems related to the design of robust HF networks- 1.) The Network Reliability Problem, which seeks to compute the …
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Power analysis for a mixed effects logistic regression model
… studies, the mixed effects logistic regression model with random herd effects are commonly used for modeling clustered binary data. These models are well developed and widely used in the literature, among which is the logistic-normal regression model. In contrast to the rich literature in …
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Estimation Of The Scale Matrix Of A Multivariate T-model
… Analysis is primarily based on the multivariate normal model. However, in the recent literature several authors have made studies as to how the conclusions will be affected if the population model departs from normality. The class of elliptical models shares some intrinsic properties of the …
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A Comparison of Methods for Generating Bivariate Non-normally Distributed Random Variables
… multivariate data in the real world follow a non-normal model with distributions being skewed and/or heavy tailed. In studies in which multivariate non-normal distributions are needed, it is important for simulations of those variables to provide data that is close to the desired parameters while …
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Exponentially Weighted Moving Average Charts for Monitoring the Process Generalized Variance
… is studied under the independent multivariate normal model for the vector of quality measurements. The performance of the chart is based on an analysis of the chart's initial and steady-state run length distributions. The three methods that are commonly used to determinate run length …
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Linear Mixed Models With Non-Normal Distributions
Linear mixed models based on the normality assumption are widely used in health related studies. Although the normality assumption leads to simple, mathematically tractable, and powerful tests, violation of the assumption may easily invalidate the statistical inference. In this dissertation, we …
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Approaches to Joint Base Station Selection and Adaptive Slicing in Virtualized Wireless Networks
… are presented for approximating the stochastic model. The first method uses a sampling approach applied to the deterministic equivalent program of the stochastic model. The second method uses a genetic algorithm for base station selection and adaptively slicing via a single-stage linear …
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Macroeconomic Forecasting: Statistically Adequate, Temporal Principal Components
… At the outset, PCA is viewed as a statistical model derived from the reparameterization of the Multivariate Normal model in Spanos (1986). To motivate a PCA forecasting framework prioritizing sound model assumptions, it is demonstrated, through simulation experiments, that model …
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Testing for Constancy of Correlation in Autoregressive Conditional Heteroscedasticity (Arch) Models
… the constancy of correlation in the multivariate normal model. Following Chesher (1984) and Cox (1983), we focus on deriving a score test of the hypothesis that the variance of the parameter of interest is zero. Here the score test checks the local behavior of the log-likelihood function close to …
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Methods for Comparing Two Means with Application in Adaptive Clinical Trials
In the design of a clinical trial, the study of the effect of an intervention for a given medical condition is frequently of interest to researcher. Also, in recent years, the use of sequential and adaptive design methods in clinical research and development based on accrued data has become very …
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Semi-parametric models for response times and response accuracy in computerized testing
… responses. This broadens the scope of potential modeling approaches because response times can be analyzed in addition to analyzing the responses themselves. Current models for response times,however, mainly focus on parametric models that have the advantage of conciseness, but may suffer from a …
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Extinction and recovery dynamics of Triassic-Jurassic macro-invertebrate communities
… were tested against five rank abundance (RAD) models. Ecospace modelling was used to estimate the loss in ecological diversity. Measures of the body size of bivalves and ichno-parameters were recorded on each section. Through the UK sections, the richness, dominance and the composition rate …
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Probabilistic Modeling of Multi-relational and Multivariate Discrete Data
Modeling and discovering knowledge from multi-relational and multivariate discrete data is a crucial task that arises in many research and application domains, e.g. text mining, intelligence analysis, epidemiology, social science, etc. In this dissertation, we study and address three problems …
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Statistical modelling of the association between dietary diversity, dietary patterns and non-communicable diseases in Namibia
… the study aimed at: (i) applying count models on dietary diversity in Namibia, (ii) using bivariate count modelling approach in analyzing convenience and non-convenience consumption food preference in Windhoek, (iii) applying copula joint modelling of food insecurity indicators with …
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Compositional models for mutational signature analysis
… Approach: I introduce appropriate compositional models to analyse two types of mutational signature: single-nucleotide polymorphism signatures, and copy number signatures. The Dirichlet-multinomial mixed effects model for single-nucleotide data is shown to have good sensitivity compared to …
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Three papers in urban and regional economic and development
… theory. In this chapter, the finite mixture model is introduced as a new exploratory method to study the regional growth issue. This study finds the emergence of convergence clubs in the United States since the 1980s. The finite mixture normal model is used to identify the clubs based on the …
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Essays on Characterizing Inefficiency for Stochastic Frontier Models
… consists of three essays on stochastic frontier models in characterizing inefficiency for a cross section of firms in essays one and three and a set of firms overtime in essay two. The first essay looks at stationary points for several models used in stochastic frontier analysis. The second essay …