Bayesian analysis of Box-Cox transformed linear mixed models with ARMA(p, q) dependence

Jack C. Lee, Tsung I. Lin, Kuo J. Lee, Ying L. Hsu

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

In this paper, we present a Bayesian inference methodology for Box-Cox transformed linear mixed model with ARMA(p, q) errors using approximate Bayesian and Markov chain Monte Carlo methods. Two priors are proposed and put into comparisons in parameter estimation and prediction of future values. The advantages of Bayesian approach over maximum likelihood method are demonstrated by both real and simulated data.

Original languageEnglish
Pages (from-to)435-451
Number of pages17
JournalJournal of Statistical Planning and Inference
Volume133
Issue number2
DOIs
Publication statusPublished - 2005 Aug 1

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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