Estimation and Prediction of Generalized Growth Curve with Grouping Variances in AR(q) Dependence Structure
✍ Scribed by Jack C. Lee; Ying-Lin Hsu
- Publisher
- John Wiley and Sons
- Year
- 2003
- Tongue
- English
- Weight
- 157 KB
- Volume
- 45
- Category
- Article
- ISSN
- 0323-3847
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✦ Synopsis
In this paper we consider maximum likelihood analysis of generalized growth curve model with the Box-Cox transformation when the covariance matrix has AR(q) dependence structure with grouping variances. The covariance matrix under consideration is S = D s CD s where C is the correlation matrix with stationary autoregression process of order q, q < p and D s is a diagonal matrix with p elements divided into gð pÞ groups, i.e., D s is a function of fs 1 ; . . . ; s g g and À1 < q < 1 and s l , l ¼ 1; . . . ; g, are unknown. We consider both parameter estimation and prediction of future values. Results are illustrated with real and simulated data.