"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.
Antle, Charles E.
Lee Ralph E.
Rivers, Jack L.
Harkness, William L.
Bain, Lee J., 1939-
Mathematics and Statistics
Ph. D. in Mathematics
National Science Foundation (U.S.)
University of Missouri--Rolla
ix, 83 pages
© 1969 Robert Henry Dumonceaux, All rights reserved.
Dissertation - Open Access
Library of Congress Subject Headings
Mathematical statistics -- Methodology
Print OCLC #
Electronic OCLC #
Link to Catalog Recordhttp://laurel.lso.missouri.edu/record=b1067258~S5
Dumonceaux, Robert Henry, "Statistical inferences for location and scale parameter distributions" (1969). Doctoral Dissertations. 2273.