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 language | English |
|---|---|
| Pages (from-to) | 435-451 |
| Number of pages | 17 |
| Journal | Journal of Statistical Planning and Inference |
| Volume | 133 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2005 Aug 1 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Applied Mathematics
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Lee, J. C., Lin, T. I., Lee, K. J., & Hsu, Y. L. (2005). Bayesian analysis of Box-Cox transformed linear mixed models with ARMA(p, q) dependence. Journal of Statistical Planning and Inference, 133(2), 435-451. https://doi.org/10.1016/j.jspi.2004.03.015