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Title:  Complete classes of twostage estimation procedures for certain finite sample problems 
Author(s):  Lee, Albert FuYuan 
Doctoral Committee Chair(s):  Marden, John I. 
Department / Program:  Statistics 
Discipline:  Statistics 
Degree Granting Institution:  University of Illinois at UrbanaChampaign 
Degree:  Ph.D. 
Genre:  Dissertation 
Subject(s):  Statistics 
Abstract:  Twostage Bayes procedures, also known as Bayes double sample procedures, for estimating the mean of exponential family distributions are given by Cohen and Sackrowitz (1984). In their study, they develop double sample Bayes estimation procedures for the mean of exponential family distributions with respect to conjugate prior distributions. The procedures consist of stating $n\sb1$, the size of the first sample; $n\sb2$, the size of the second sample which depends on the data from the first sample; and finally the point estimate, which depends on the combined sample. The loss functions usually are linear combinations of loss due to terminal decision and loss due to sampling. They find the optimal second sample size as well as the optimal first sample size. In our study, the first sample size is fixed and the second sample is determined by discrete search, which is different from their determination. The admissibility of a generalized Bayes procedure with respect to an improper prior is investigated using Blyth's limiting Bayes method (1952) and Brown's totally Bayes method (1981). A complete class for twostage estimation of the parameter p of the binomial distribution is obtained. In the several binomial distributions situation, we find the twostage Bayes procedures for estimating the difference of two binomial parameters with respect to two independent prior distributions. The admissibility of a generalized Bayes procedure with respect to two independent improper prior distributions is investigated using Blyth's method and Brown's method. An analogous complete class theorem is obtained. Finally, we look at the multinomial situation. The prior distribution is now Dirichlet with ($\alpha\sb1$,$\alpha\sb2$,$\...$,$\alpha\sb{k}$) and the loss function is $\sum\sbsp{i = 1}{k}$($\ p\sb{i} \ p\sb{i})\sp2 +\ c(n\sb1 +\ n\sb2)$. We find the twostage Bayes procedures with respect to Dirichlet prior when k = 3. The admissibility of the procedure when $\alpha\sb1$ = $\alpha\sb2$ = $\alpha\sb3$ = 0 is obtained by a totally Bayes procedure with respect to a sequence of fiveprior distributions. We also find a complete class theorem. 
Issue Date:  1990 
Type:  Text 
Language:  English 
URI:  http://hdl.handle.net/2142/20431 
Rights Information:  Copyright 1990 Lee, Albert FuYuan 
Date Available in IDEALS:  20110507 
Identifier in Online Catalog:  AAI9114307 
OCLC Identifier:  (UMI)AAI9114307 
This item appears in the following Collection(s)

Graduate Dissertations and Theses at Illinois
Graduate Theses and Dissertations at Illinois 
Dissertations and Theses  Statistics