Doctoral Dissertations

Abstract

"The problem of discriminating between two location and scale parameter distributions is investigated. A general test based on a ratio of likelihoods is presented. A test based on a Pearson Goodness of Fit statistic is also considered. Tables are given for discriminating between the normal and exponential, the normal and double exponential, the normal and extreme value, and also between the normal and logistic. For location and scale parameter distributions, two-sided tolerance limits are shown to always be obtainable by Monte Carlo simulation. A method for obtaining confidence intervals on the reliability at a fixed time t is also given. Maximum likelihood estimators, based on type II censored samples from the normal, are used to obtain tables required for statistical inference about the parameters µ and Δ. Unbiased estimators based on the maximum likelihood estimators are given. The iterative methods used for obtaining the maximum likelihood estimators are discussed and means of obtaining starting values are presented"--Abstract, page ii.

Advisor(s)

Antle, Charles E.

Committee Member(s)

Haddock, Glen
Lee Ralph E.
Rivers, Jack L.
Harkness, William L.
Bain, Lee J., 1939-

Department(s)

Mathematics and Statistics

Degree Name

Ph. D. in Mathematics

Sponsor(s)

National Science Foundation (U.S.)

Publisher

University of Missouri--Rolla

Publication Date

1969

Pagination

ix, 83 pages

Note about bibliography

Includes bibliographical references (pages 69-70).

Rights

© 1969 Robert Henry Dumonceaux, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Library of Congress Subject Headings

Mathematical statistics
Mathematical statistics -- Methodology
Estimation theory

Thesis Number

T 2300

Print OCLC #

6013130

Electronic OCLC #

833161232

Included in

Mathematics Commons

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