11. Multiple Regression: Bayesian Inference

  1. Alvin C. Rencher and
  2. G. Bruce Schaalje

Published Online: 30 APR 2007

DOI: 10.1002/9780470192610.ch11

Linear Models in Statistics, Second Edition

Linear Models in Statistics, Second Edition

How to Cite

Rencher, A. C. and Schaalje, G. B. (2007) Multiple Regression: Bayesian Inference, in Linear Models in Statistics, Second Edition, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470192610.ch11

Author Information

  1. Department of Statistics, Brigham Young University, Provo, Utah, USA

Publication History

  1. Published Online: 30 APR 2007
  2. Published Print: 14 DEC 2007

ISBN Information

Print ISBN: 9780471754985

Online ISBN: 9780470192610

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Keywords:

  • joint posterior density or marginal posterior density;
  • multiple linear regression models;
  • closed-form density functions

Summary

This chapter contains sections titled:

  • Elements of Bayesian Statistical Inference

  • A Bayesian Multiple Linear Regression Model

  • Inference in Bayesian Multiple Linear Regression

  • Bayesian Inference through Markov Chain Monte Carlo Simulation

  • Posterior Predictive Inference

  • Problems