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On Empirical Bayes Selection Rules for Negative Binomial Populations

On Empirical Bayes Selection Rules for Negative Binomial Populations
Author: Shanti S. Gupta
Publisher:
Total Pages: 30
Release: 1988
Genre:
ISBN:

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This paper deals with the problem of selecting good negative binomial populations as compared with a standard or a control. The main results are based on the use of the empirical Bayes approach. First the authors derive the monotone empirical Bayes estimators of the concerned parameters. Based on these estimators, they construct monotone empirical Bayes selection rules. Asymptotic optimality properties of the monotone empirical Bayes estimators and the monotone empirical Bayes selection rules are investigated. The respective convergence rates for the estimation problem and for the selection problem are studied, under some conditions. (KR).


Empirical Bayes Rules for Selecting the Best Binomial Population

Empirical Bayes Rules for Selecting the Best Binomial Population
Author: Shanti S. Gupta
Publisher:
Total Pages: 24
Release: 1986
Genre:
ISBN:

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Some selection rules based on monotone empirical Bayes estimators of the binomial parameters are proposed. First, it is shown that, under the squared error loss, the Bayes risks of the proposed monotone empirical Bayes estimators converge to the related minimum Bayes risks with rates of convergence at least of order 0(nsub -n), where n is the number of accumulated past experiences at hand. Further, for the selection problem, the rates of convergence of the proposed selection rules are shown to be at least of order 0(exp( -cn)) for some c> 0. Keywords: Asymptotically optimal.


Empirical Bayes Rules for Selecting Good Binomial Populations. Revision

Empirical Bayes Rules for Selecting Good Binomial Populations. Revision
Author: Shanti S. Gupta
Publisher:
Total Pages: 24
Release: 1985
Genre:
ISBN:

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This paper deals with the problem of selecting good binomial populations compared with a standard or a control through the empirical Bayes approach. Two cases have been studied: one with the pior distribution completely unknown and the other with the prior distribution symmetrical about p = 1/2, but otherwise unknown. In each case, empirical Bayes rules are derived and their rates of convergence are shown to be of order O(exp( -cn)) for some c>O, where n is the number of accumulated post experiences at hand. Keywords: Statistical decision theory; Smoothing(Mathematics); Asymptotically optimal. (Author).


Empirical Bayes Rules for Selecting Good Binomial Populations

Empirical Bayes Rules for Selecting Good Binomial Populations
Author: S. S. Gupta
Publisher:
Total Pages: 32
Release: 1984
Genre:
ISBN:

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This paper deals with the problem of selecting good binomial populations compared with a standard or a control through the empirical Bayes approach. Two cases have been studied: one is that the prior distribution is completely unknown and the other is that the prior distribution is symmetrical about p = 1/2, but its form is still unknown. In each case, empirical Bayes rules are derived and the rate of convergence of corresponding empirical Bayes rules is also studied.


Bayesian Analysis in Statistics and Econometrics

Bayesian Analysis in Statistics and Econometrics
Author: Prem K. Goel
Publisher: Springer Science & Business Media
Total Pages: 409
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461229448

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This volume is based on the invited and the contributed presentations given at the Indo-U.S. Workshop on Bayesian Analysis in Statistics and Econometrics (BASE), Dec. 19-23, 1988, held at the Hotel Taj Residency, Bangalore, India. The workshop was jointly sponsored by The Ohio State University, The Indian Statistical Institute, The Indian Econometrics So ciety, U.S. National Science Foundation and the NSF-NBER Seminar on Bayesian Inference in Econometrics. Profs. Morrie DeGroot, Prem Goel, and Arnold Zellner were the program organizers. Unfortunately, Morrie became seriously ill just before the workshop was to start and could not participate in the workshop. Almost a year later, Morrie passed away after fighting valiantly with the illness. Not to find Morrie among ourselves was a shock for most of us. He was a continuous source of inspiration and ideas. Even while Morrie was fighting for his life, we had a lot of discussions about the contents of this volume and the Bangalore Workshop. He even talked about organizing a Second Indo-U.S. workshop some time in the near future. We are dedicating this volume to the memory of Prof. Morris H. DeGroot. We have taken a conscious decision not to include any biography of Morrie in this volume. An excellent biography of Morrie has appeared in Statistical Science [(1991), vol. 6, 1-14], and we could not have done a better job than that.


Scientific and Technical Aerospace Reports

Scientific and Technical Aerospace Reports
Author:
Publisher:
Total Pages: 976
Release: 1990
Genre: Aeronautics
ISBN:

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Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.


Empirical Bayes Rules for Selecting Good Populations

Empirical Bayes Rules for Selecting Good Populations
Author: Shanti Swarup Gupta
Publisher:
Total Pages: 21
Release: 1981
Genre: Bayesian statistical decision theory
ISBN:

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A problem of selecting populations better than a control is considered. When the populations are uniformly distributed, empirical Bayes rules are derived for a linear loss function for both the known control parameter and the unknown control parameter cases. When the priors are assumed to have bounded supports, empirical Bayes rules for selecting good populations are derived for distributions with truncation parameters (i.e. the form of the pdf is f(x/theta) = Pi(x)ci(theta)I(O, theta)(x)). Monte Carlo studies are carried out which determine the minimum sample sizes needed to make the relative errors less than epsilon for given epsilon-values. (Author).