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Articles

Wavelet threshold based on Stein's unbiased risk estimators of restricted location parameter in multivariate normal

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Pages 1712-1729 | Received 21 Aug 2019, Accepted 17 May 2020, Published online: 09 Jun 2020
 

Abstract

In this paper, the problem of estimating the mean vector under non-negative 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.

Acknowledgments

The support of Research Committee of Persian Gulf University is greatly acknowledged.

Disclosure statement

No potential conflict of interest was reported by the authors.

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