Mixed model representation of state space models: New smoothing results and their application to REML estimation

Statistica Sinica

Volumn 7, Issue 4, 1997, Pages 973-991

  Tsimikas, John V ^a   Ledolter, Johannes ^b  

^a UNIVERSITY OF MASSACHUSETTS   (United States)

^b UNIVERSITY OF IOWA   (United States)

Author keywords

Diffuse prior distribution; EM algorithm; Kalman filter; Mixed model prediction; Restricted maximum likelihood; State space model; Variance components

Indexed keywords

EID: 0031326632     PISSN: 10170405     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (9)

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4. Goodnight, J. H. (1979). A tutorial on the SWEEP operator. Amer. Statist. 33, 149-158.
5. Harvey, A. C. (1989). Forecasting, Structural Time Series Models and the Kaiman Filter. Cambridge: Cambridge University Press.
6. Jones, R. H. (1993). Longitudinal Data with Serial Correlation: A State Space Approach. Chapman Hall, London.
7. Kass, R. E. and Steffey, D. (1989). Approximate Bayesian inference in conditionally independent hierarchical models (Parametric empirical Bayes models). J. Amer. Statist. Assoc. 84, 717-726.
8. Sallas, ,W. M. and Harville, D. A. (1981). Best linear recursive estimation for mixed linear models. J. Amer. Statist. Assoc. 76, 860-869.
9. Searle, S. R., Casella, G. and McCulloch, C. E. (1992). Variance Components. John Wiley, New York.