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The Extraction of Information From Multiple Point Estimates

El-Gamal, Mahmoud (1993) The Extraction of Information From Multiple Point Estimates. Social Science Working Paper, 839. California Institute of Technology , Pasadena, CA. (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20170825-142324974

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Abstract

The use of a number of point estimation experiments to construct a least informative prior subject to the information in the estimation experiments is studied. The form of the resulting prior is established. The prior depends on parameters that result from solving a calculus of variations problem. It is shown that simple Gibbs sampler algorithms converge to the desired solution, and simulated annealing algorithms yield the mode of the prior. The Gibbs sampler algorithm is ergodic, and hence Bayes risks can be directly computed using time averages of a single series of draws from the sampler.


Item Type:Report or Paper (Working Paper)
Related URLs:
URLURL TypeDescription
http://resolver.caltech.edu/CaltechAUTHORS:20170828-152416634Related ItemPublished Version
Additional Information:Published as El-Gamal, Mahmoud A. "The extraction of information from multiple point estimates." Journaltitle of Nonparametric Statistics 2, no. 4 (1993): 369-378.
Group:Social Science Working Papers
Subject Keywords:Information theory, meta-analysis, Gibbs sampler, simulated annealing.
Series Name:Social Science Working Paper
Issue or Number:839
Record Number:CaltechAUTHORS:20170825-142324974
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170825-142324974
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:80802
Collection:CaltechAUTHORS
Deposited By: Jacquelyn Bussone
Deposited On:28 Aug 2017 21:06
Last Modified:03 Oct 2019 18:35

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