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An Extension of the Non-central Wishart Distribution with Integer Shape Vector

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Abstract

This research paper deals with an extension of the non-central Wishart introduced in 1944 by Anderson and Girshick, that is the non-central Riesz distribution when the scale parameter is derived from a discrete vector. It is related to the matrix of normal samples with monotonous missing data. We characterize this distribution by means of its Laplace transform and we give an algorithm for generating it. Then we investigate, based on the method of the moment, the estimation of the parameters of the proposed model. The performance of the proposed estimators is evaluated by a numerical study.

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Acknowledgements

I sincerely thank the Editor and the referees for their suggestions and comments that led to significant improvements in this paper.

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  1. National School of Electronics and Telecommunications of Sfax, University of Sfax, Sfax, 3018, Tunisia

    Kaouthar Kammoun

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  1. Kaouthar Kammoun
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Correspondence to Kaouthar Kammoun.

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Kammoun, K. An Extension of the Non-central Wishart Distribution with Integer Shape Vector. Acta. Math. Sin.-English Ser. (2024). https://doi.org/10.1007/s10114-024-2549-8

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