Estimation of the mean vector of a multivariate normal model under reflected normal loss

 

B. Ghari, M. Arashi, and S.M.M. Tabatabaey (2009). Estimation of the mean vector of a multivariate normal model under reflected normal loss. Journal of Statistical Research, Vol. 43, No. 1, pp.  41-52.

 

Abstract

For estimating an unknown mean vector-parameter $ {\theta} $ in a multivariate normal population, we propose the unrestricted, restricted and preliminary test estimators and derive their exact risk expressions under a modified reflected normal loss function. This approach is an extension to the work of Giles [Preliminary-Test and Bayes Estimation of A Location Parameter Under Reflected Normal Loss, in Ullah, A. and Chaturvedi, A, Handbook of Applied Econometrics and Statistical Inference, Marcel Decker, New York, 287-303, 2002]. Comparison are then made for more clarity of the behavior of the estimators.

 

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