Minimax prediction under random sample size

Alicja Jokiel-Rokita. "Minimax prediction under random sample size." Applicationes Mathematicae 29.2 (2002): 127-134. <http://eudml.org/doc/279644>.

@article{AlicjaJokiel2002,
abstract = {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.},
author = {Alicja Jokiel-Rokita},
journal = {Applicationes Mathematicae},
keywords = {admissibility; ancillarity paradox; loss function; minimax predictor; multinomial distribution; multivariate hypergeometric distribution; risk function},
language = {eng},
number = {2},
pages = {127-134},
title = {Minimax prediction under random sample size},
url = {http://eudml.org/doc/279644},
volume = {29},
year = {2002},
}

TY - JOUR
AU - Alicja Jokiel-Rokita
TI - Minimax prediction under random sample size
JO - Applicationes Mathematicae
PY - 2002
VL - 29
IS - 2
SP - 127
EP - 134
AB - 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.
LA - eng
KW - admissibility; ancillarity paradox; loss function; minimax predictor; multinomial distribution; multivariate hypergeometric distribution; risk function
UR - http://eudml.org/doc/279644
ER -