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Abstract
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In this paper, the problem of estimating the mean vector under nonnegative
constraints on location vector of the multivariate normal
distribution is investigated. The value of the wavelet threshold based
on Stein’s unbiased risk estimators is calculated for the shrinkage
estimator in restricted parameter space. We suppose that covariance
matrix is unknown and we find the dominant class of shrinkage estimators
under Balance loss function. The performance evaluation of
the proposed class of estimators is checked through a simulation
study by using risk and average mean square error values
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