Journal article
Analysis of Multi-Unit Variance Components Models with State Space Profiles
Annals of the Institute of Statistical Mathematics, Vol.50(1), pp.147-164
03/01/1998
DOI: 10.1023/A:1003405615641
Abstract
We apply the Kalman Filter to the analysis of multi-unit variance components models where each unit's response profile follows a state space model. We use mixed model results to obtain estimates of unit-specific random effects, state disturbance terms and residual noise terms. We use the signal extraction approach to smooth individual profiles. We show how to utilize the Kalman Filter to efficiently compute the restricted loglikelihood of the model. For the important special case where each unit's response profile follows a continuous structural time series model with known transition matrix we derive an EM algorithm for the restricted maximum likelihood (REML) estimation of the variance components. We present details for the case where individual profiles are modeled as local polynomial trends or polynomial smoothing splines.
Details
- Title: Subtitle
- Analysis of Multi-Unit Variance Components Models with State Space Profiles
- Creators
- John V. Tsimikas - Harvard Medical SchoolJohannes Ledolter - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Annals of the Institute of Statistical Mathematics, Vol.50(1), pp.147-164
- DOI
- 10.1023/A:1003405615641
- ISSN
- 0020-3157
- eISSN
- 1572-9052
- Language
- English
- Date published
- 03/01/1998
- Academic Unit
- Statistics and Actuarial Science; Business Analytics
- Record Identifier
- 9984380397702771
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