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Admissable and minimax procedures in statistical estimation

"The purpose of this paper is to present two methods for proving that a statistical estimate is admissible and minimax. The Bayes method was introduced by Wald, and Theorems 2.2 and 2.3 illustrate the technique. The second way is due to Hodges and Lehmann and is based on a lower bound for the variance of an estimate. In Theorem 3.2 the Hodges-Lehmann method for proving admissibility is given. The last chapter is devoted to an extension of the Hodges and Lehmann technique to the Bhattacharyya bounds"--Introduction. / "August, 1954." / Typescript. / "Submitted to the Graduate Council of Florida State University in partial fulfillment of the requirements for the degree of Master of Science." / Advisor: A. V. Fend, Professor Directing Paper. / Includes bibliographical references (leaves 44-45).

Identiferoai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_257281
ContributorsEdwards, Anna Caroline (authoraut), Fend, A. V. (professor directing thesis.), Florida State University (degree granting institution)
PublisherFlorida State University, Florida State University
Source SetsFlorida State University
LanguageEnglish, English
Detected LanguageEnglish
TypeText, text
Format1 online resource (iii, 45 leaves), computer, application/pdf
RightsThis Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them.

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