A Bayesian Approach to Two-Stage Sampling.

Abstract

In several previous papers, the author has shown that various standard sampling designs are optimal in a Bayesian sense under corresponding classes of prior distributions on the N-dimensional vector of unknown characteristics of the N elements of a finite population. In this manner a Bayesian interpretation of simple random sampling, stratified random sampling, and of various ratio and regression estimators have been given. In the present report this work is extended to two-stage balanced sampling. Additionally, a simple result on a representation of finitely exchangeable discrete random variables is given which gives a slight generalization of a seemingly little-known result of de Finetti. Also a general tie between Bayes posterior means and traditional WLSE's and BLUE's is obtained, generalizing previous results given by the author. (Author)

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1976
Accession Number
ADA025624

Entities

People

  • W. A. Ericson

Organizations

  • University of Michigan

Tags

DTIC Thesaurus Topics

  • Bayesian Networks
  • Collecting Methods
  • Estimators
  • Mathematics
  • Probabilistic Models
  • Random Variables
  • Sampling
  • Standards
  • Statistical Sampling

Fields of Study

  • Mathematics

Readers

  • Mathematical Modeling and Probability Theory.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference