Geodesic
Minimax prediction under random sample size
Alicja Jokiel-Rokita1
1 Institute of Mathematics Wrocław University of Technology 50-370 Wrocław, Poland
Applicationes Mathematicae, Tome 29 (2002) no. 2, pp. 127-134 Cet article a éte moissonné depuis la source Institute of Mathematics Polish Academy of Sciences

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A class of minimax predictors of random variables with multinomial or multivariate hypergeometric distribution is determined in the case when the sample size is assumed to be a random variable with an unknown distribution. It is also proved that the usual predictors, which are minimax when the sample size is fixed, are not minimax, but they remain admissible when the sample size is an ancillary statistic with unknown distribution.
DOI : 10.4064/am29-2-1
Keywords: class minimax predictors random variables multinomial multivariate hypergeometric distribution determined sample size assumed random variable unknown distribution proved usual predictors which minimax sample size fixed minimax remain admissible sample size ancillary statistic unknown distribution

Alicja Jokiel-Rokita 1

1 Institute of Mathematics Wrocław University of Technology 50-370 Wrocław, Poland 
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Alicja Jokiel-Rokita. Minimax prediction
  under random sample size. Applicationes Mathematicae, Tome 29 (2002) no. 2, pp. 127-134. doi: 10.4064/am29-2-1

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