Advertisement

Effect of auto-correlations on the optimum allocations in two phase stratified sampling—A bayesian approach

  • Irwin Guttman
  • Charles D. Palit
Article
  • 32 Downloads

Abstract

In this paper we study the problem of optimal allocation when the model for generation of observations in a particular stratum permits for auto-correlations. The object of the study is assumed to be the estimation of the population mean as precisely as possible.

Keywords

Posterior Distribution Optimum Allocation Phase Sample Future Expectation Phase Observation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Draper, N. R. and Guttman, Irwin (1968a). Some Bayesian stratified two-phase sampling results,Biometrika,55, 131–139.CrossRefMathSciNetGoogle Scholar
  2. [2]
    Draper, N. R. and Guttman, Irwin (1968b). Bayesian stratified two-phase sampling results:k characteristics,Biometrika,55, 587–589.CrossRefMathSciNetGoogle Scholar
  3. [3]
    Guttman, Irwin and Palit, C. D. (1971a). Optimal allocation for two-phase stratified samples when the within stratum observations are correlated—A Bayesian approach I. Known correlation—A sensitivity study,Technical Report No. 128, Centre de Recherches Mathématiques, Université de Montréal.Google Scholar
  4. [4]
    Guttman, Irwin and Palit, C. D. (1971b). Optimal allocation for two-phase stratified samples when the within stratum observations are correlated—A Bayesian approach II. Unknown correlation,Technical Report No. 129, Centre de Recherches Mathématiques, Université de Montréal.Google Scholar
  5. [5]
    Guttman, Irwin and Palit, C. D. (1972). Auto correlations and effect on optimum allocation—A Bayesian approach,Technical Report No. 130, Centre de Recherches Mathématiques, Université de Montréal.Google Scholar
  6. [6]
    Jenkins, G. M. and Watts, D. G. (1968).Spectral Analysis and Its Applications, Holden Day, San Francisco, California.zbMATHGoogle Scholar
  7. [7]
    Kendall, M. G. and Stuart, A. (1966).The Advanced Theory of Statistics, Vol. 3, Griffin and Co., London.Google Scholar
  8. [8]
    Raiffa, H. and Schlaifer, R. (1961).Applied Statistical Decision Theory, Division of Research, Harvard Business School, Harvard University, Boston.Google Scholar
  9. [9]
    Tiao, G. C. and Tan, W. Y. (1966). Bayesian analysis of random-effect models in the analysis of variance II. Effect of autocorrelated errors,Biometrika,53, 477–495.CrossRefMathSciNetGoogle Scholar
  10. [10]
    Zellner, A. and Tiao, G. C. (1964). Bayesian analysis of the regression model with autocorrelated errors,J. Amer. Statist. Ass.,59, 763–768.CrossRefMathSciNetGoogle Scholar

Copyright information

© The Institute of Statistical Mathematics 1975

Authors and Affiliations

  • Irwin Guttman
    • 1
    • 2
  • Charles D. Palit
    • 1
    • 2
  1. 1.University of TorontoTorontoCanada
  2. 2.University of WisconsinUSA

Personalised recommendations