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Decision theoretic analysis of spherical regression

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  • Kim, Peter T.

Abstract

Spherical regression in a decision theoretic framework is examined, where the data is observed on S2 with the parameter space being SO(3). Bayes estimators are characterized under squared error loss on SO(3) as well as conditions under which the least squares estimator is a Bayes estimator with respect to the Haar prior. Under continuity conditions and the compactness of SO(3), a Bayes estimator is admissible. Thus the least squares estimator is admissible.

Suggested Citation

  • Kim, Peter T., 1991. "Decision theoretic analysis of spherical regression," Journal of Multivariate Analysis, Elsevier, vol. 38(2), pages 233-240, August.
    • Handle: RePEc:eee:jmvana:v:38:y:1991:i:2:p:233-240
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    Cited by:

    1. Oualkacha, Karim & Rivest, Louis-Paul, 2009. "A new statistical model for random unit vectors," Journal of Multivariate Analysis, Elsevier, vol. 100(1), pages 70-80, January.
    2. Hendriks, Harrie, 2005. "The admissibility of the empirical mean location for the matrix von Mises-Fisher family," Journal of Multivariate Analysis, Elsevier, vol. 92(2), pages 454-464, February.

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