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Generalized Bayes Stein-Type Estimators for Regression Parameters under Linear Constraints

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  • Hoffmann, K.

Abstract

The problem of estimating the k-dimensional parameter vector in a linear regression model with m linear restrictions is considered. The proposed estimators are generalized Bayes with respect to a prior distribution compatible with the linear restrictions. Under certain conditions some of the generalized Bayes estimators dominate the ordinary least-squares estimator and are admissible.

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  • Hoffmann, K., 1993. "Generalized Bayes Stein-Type Estimators for Regression Parameters under Linear Constraints," Journal of Multivariate Analysis, Elsevier, vol. 46(1), pages 120-130, July.
    • Handle: RePEc:eee:jmvana:v:46:y:1993:i:1:p:120-130
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    Cited by:

    1. Michelle R. Danaher & Anindya Roy & Zhen Chen & Sunni L. Mumford & Enrique F. Schisterman, 2012. "Minkowski--Weyl Priors for Models With Parameter Constraints: An Analysis of the BioCycle Study," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1395-1409, December.

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