Statistical estimation by the empirical Bayes method: some extensions and logistical applications

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Presentation of the empirical Bayes procedure for improving existing methods of estimating statistical decision parameters which occur in such logistical problems as reliability, maintenance, and supply. It consists essentially of estimating a parameter by using an approximate Bayes estimator that does not depend on any previous information, other than earlier observations. The author presents estimators for the univariate and multivariate exponential family of distributions, for distributions with nuisance parameters, and for the distribution of a family of random variables (Poisson process).

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Format:
Paperback, 46 Pages
Year:
1965
List Price:
$23.00
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Document Details

  • Availability: Available
  • Format: Paperback
  • Pages: 46
  • List Price: $23.00
  • Price: $18.40
  • Document Number: RM-4442-PR
  • Year: 1965
  • Series: Research Memoranda

This report is part of the RAND Corporation research memorandum series. The Research Memorandum was a product of the RAND Corporation from 1948 to 1973 that represented working papers meant to report current results of RAND research to appropriate audiences.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.

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