A note on spectral decomposition and maximum likelihood estimation in models with balanced data
AbstractA simple derivation of the spectral decomposition of the covariance matrix for a general multi-way variance components model is presented. So-called balanced data are assumed to be available. Spectral decomposition is exploited to derive the information matrix and the first-order conditions for the maximum likelihood estimation of the variance components parameters.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 1 (1983)
Issue (Month): 4 (June)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Badi H. Baltagi & Long Liu, 2012.
"Estimation and Prediction in the Random Effects Model with AR(p) Remainder Disturbances,"
Center for Policy Research Working Papers
138, Center for Policy Research, Maxwell School, Syracuse University.
- Baltagi, Badi H. & Liu, Long, 2013. "Estimation and prediction in the random effects model with AR(p) remainder disturbances," International Journal of Forecasting, Elsevier, vol. 29(1), pages 100-107.
- Théophile AZOMAHOU & Phu NGUYEN VAN & Marcus WAGNER, 2001. "Determinants of Environmental and Economic Performance of Firms: An Empirical Analysis of the European Paper Industry," Working Papers of BETA 2001-22, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
- Badi Baltagi & Dong Li, 2006.
"Prediction in the Panel Data Model with Spatial Correlation: the Case of Liquor,"
Spatial Economic Analysis,
Taylor & Francis Journals, vol. 1(2), pages 175-185.
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"Behavioral responses to risk in rural China,"
Journal of Development Economics,
Elsevier, vol. 66(1), pages 23-49, October.
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