Bayes Estimates of the Variance of a Normal Population for Prior Conjugate Distributions of Independent Parameters with application to Estimation in Finite Populations.

Abstract

A Byes estimator of the variance of a normal distribution n(mu, sigma-squared), when mu is unknown, is developed for squared-error loss and conjugate priors of independent parameters. In the present study its formula is developed and its relative efficiency is compared with that of the Bayes estimator and with that of the best equivariant estimator. Application of the estimator to the estimation of the variance of a finite population is provided.

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Document Details

Document Type
Technical Report
Publication Date
Jan 10, 1979
Accession Number
ADA064916

Entities

People

  • Shelemyahu Zacks

Organizations

  • Case Western Reserve University

Tags

DTIC Thesaurus Topics

  • Bayesian Inference
  • Bayesian Networks
  • Data Science
  • Efficiency
  • Estimators
  • Information Science
  • Mathematics
  • Military Research
  • Models
  • New York
  • Normal Distribution
  • Procedures (Computers)
  • Random Variables
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Inference
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Statistical inference.