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Minimum average risk and efficiency of optimal polynomial multidimensional-matrix predictors

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Abstract

Statistical decision theory is used to consider the problem of estimating (predicting) a random multidimensional matrix based on the measurement of another random multidimensional matrix in the case of quadratic loss function. An expression for the minimum average risk for the optimal polynomial multidimensional-matrix predictor is derived. The properties of such a predictor are proved and the concept of its efficiency is introduced.

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References

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Authors and Affiliations

  1. Belarus State University of Informatics and Radioelectronics, Minsk, Belarus

    V. S. Mukha

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  1. V. S. Mukha
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Correspondence to V. S. Mukha.

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Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 121–130, March–April 2011.

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Mukha, V.S. Minimum average risk and efficiency of optimal polynomial multidimensional-matrix predictors. Cybern Syst Anal 47, 277–285 (2011). https://doi.org/10.1007/s10559-011-9309-3

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  • DOI: https://doi.org/10.1007/s10559-011-9309-3

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