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Faculty of Graduate Studies and Research, University of Regina

Inconsistency of Statistical Tests to Discriminate Lifetime Distributions and lines of Indistinguishabilty in Uniform Metric

Abstract

dc:description.abstract

The lifetime of a product can be measured in miles, hours, cycles or any other metric that applies to the success of a particular product. The lifetime distribution method is widely used in the engineering and biomedical applications; In this thesis, I focus on the three most commonly used lifetime distributions: Gamma distribution, Weibull distribution, and Generalized Exponential distribution. Although all three distributions have successfully served as population models for evaluating the lifetime of product, they have different characteristics. Therefore, it is necessary to distinguish the correct model specifications in the lifetime analysis. My thesis investigates the inconsistency of the statistical test to discriminate between these lifetime distributions and lines of indistinguishability in the uniform metric.

Degree

thesis:*
Name thesis:degree_name
Master of Science (MSc)
Level thesis:degree_level
Master's
Discipline thesis:degree_discipline
Statistics
Grantor dc:publisher
Faculty of Graduate Studies and Research, University of Regina
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Liu, Jingwen
Advisors dc:contributor.advisor
  • Volodin, Andrei
  • Bae, Taehan
Committee member dc:contributor.committeemember
  • Camochan Naqvi, Sarah

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:uregina.scholaris.ca:10294/9256

Chain of custody

source
Harvested from
University of Regina
Base URL
uregina.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Liu, Jingwen. Inconsistency of Statistical Tests to Discriminate Lifetime Distributions and lines of Indistinguishabilty in Uniform Metric. Master's thesis, Faculty of Graduate Studies and Research, University of Regina, 2019. https://hdl.handle.net/10294/9256