Item Details

Numerical Issues in Estimation of Continuous Parametric Distributions

Zhang, Yiwei
Format
Thesis/Dissertation; Online
Author
Zhang, Yiwei
Advisor
Krzysztofowicz, Roman
Abstract
Continuous variates are used everywhere (almost) in stochastic modeling. This thesis addresses numerical issues arising in the process of estimating a continuous parametric distribution function. It aims to provide a guide to analysts on how to overcome some problems we have encountered. In detail, it (1) applies the uniform method for estimating a one- or two-parameter distribution function from a complete sample; (2) derives the Conditional Empirical Distribution method for estimating distribution function from a censored sample (of any type); (3) illustrates the superiority of the Conditional Empirical Distribution method over the Maximum Likelihood Estimation method; (4) determines the reason for difficulties (unbounded solutions) in optimization of Pareto distribution parameters; (5) demonstrates the fallacy of applying the goodness-of-fit tests meant for discrete distributions, such as the chi-square test, to continuous distributions.
Language
English
Date Received
20120505
Published
University of Virginia, Department of Systems Engineering, MS (Master of Science), 2012
Published Date
2012-04-27
Degree
MS (Master of Science)
Collection
Libra ETD Repository
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