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Bayesian analysis of a general growth curve model with predictions using power transformations and AR(1) autoregressive dependence

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  • Jack Lee
  • Kuo-Ching Liu

Abstract

In this paper, we consider a Bayesian analysis of the unbalanced (general) growth curve model with AR(1) autoregressive dependence, while applying the Box-Cox power transformations. We propose exact, simple and Markov chain Monte Carlo approximate parameter estimation and prediction of future values. Numerical results are illustrated with real and simulated data.

Suggested Citation

  • Jack Lee & Kuo-Ching Liu, 2000. "Bayesian analysis of a general growth curve model with predictions using power transformations and AR(1) autoregressive dependence," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(3), pages 321-336.
    • Handle: RePEc:taf:japsta:v:27:y:2000:i:3:p:321-336
    DOI: 10.1080/02664760021637
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    Cited by:

    1. M. A. Alkhamisi & Ghazi Shukur, 2005. "Bayesian analysis of a linear mixed model with AR(p) errors via MCMC," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(7), pages 741-755.

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