Gamma-Minimax Prediction for the Multinomial Distribution |
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Authors: | Alicja Jokiel-Rokita |
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Institution: | (1) Institute of Mathematics and Computer Science, Wrocław University of Technology, Wrocław, Poland |
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Abstract: | Characterizations of gamma-minimax predictors for the linear combinations of the unknown parameter and the random variable having the multinomial distribution under arbitrary squared error loss are established in two situations – when the sample size is fixed and when the sample size is a realization of a random variable. It is always assumed that the available vague prior information about the unknown parameter can be described by a class of priors whose vector of first moments belongs to a suitable convex and compact set. Several known gamma-minimax and minimax results can be obtained from the characterizations derived in the present paper. |
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Keywords: | Bayes estimator Bayes risk Gamma-minimax estimation Gamma-minimax prediction Multinomial distribution |
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