9. Hierarchical Models and Bayesian Estimation

  1. Shayle R. Searle,
  2. George Casella and
  3. Charles E. McCulloch

Published Online: 27 MAY 2008

DOI: 10.1002/9780470316856.ch9

Variance Components

Variance Components

How to Cite

Searle, S. R., Casella, G. and McCulloch, C. E. (2008) Hierarchical Models and Bayesian Estimation, in Variance Components, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470316856.ch9

Publication History

  1. Published Online: 27 MAY 2008
  2. Published Print: 13 MAR 1992

ISBN Information

Print ISBN: 9780471621621

Online ISBN: 9780470316856

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Keywords:

  • mixed model;
  • estimation principles;
  • prior distribution;
  • Bayesian methodology;
  • posterior distribution

Summary

The prelims comprise:

  • Basic principles

  • Variance estimation in the normal hierarchy

  • Estimation of effects

  • Other types of hierarchies

  • Practical considerations in hierarchical modeling

  • Philosophical considerations in hierarchical modeling

  • Summary

  • Exercises