Exponential rates for the error probabilities in selection procedures
Friedrich Liese; Klaus J. Miescke
Kybernetika (1999)
- Volume: 35, Issue: 3, page [309]-332
- ISSN: 0023-5954
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topLiese, Friedrich, and Miescke, Klaus J.. "Exponential rates for the error probabilities in selection procedures." Kybernetika 35.3 (1999): [309]-332. <http://eudml.org/doc/33430>.
@article{Liese1999,
abstract = {For a sequence of statistical experiments with a finite parameter set the asymptotic behavior of the maximum risk is studied for the problem of classification into disjoint subsets. The exponential rates of the optimal decision rule is determined and expressed in terms of the normalized limit of moment generating functions of likelihood ratios. Necessary and sufficient conditions for the existence of adaptive classification rules in the sense of Rukhin [Ru1] are given. The results are applied to the problem of the selection of the best population. Exponential families are studied as a special case, and an example for the normal case is included.},
author = {Liese, Friedrich, Miescke, Klaus J.},
journal = {Kybernetika},
keywords = {generating functions of likelihood ratio; exponential family; generating functions of likelihood ratio; exponential family},
language = {eng},
number = {3},
pages = {[309]-332},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Exponential rates for the error probabilities in selection procedures},
url = {http://eudml.org/doc/33430},
volume = {35},
year = {1999},
}
TY - JOUR
AU - Liese, Friedrich
AU - Miescke, Klaus J.
TI - Exponential rates for the error probabilities in selection procedures
JO - Kybernetika
PY - 1999
PB - Institute of Information Theory and Automation AS CR
VL - 35
IS - 3
SP - [309]
EP - 332
AB - For a sequence of statistical experiments with a finite parameter set the asymptotic behavior of the maximum risk is studied for the problem of classification into disjoint subsets. The exponential rates of the optimal decision rule is determined and expressed in terms of the normalized limit of moment generating functions of likelihood ratios. Necessary and sufficient conditions for the existence of adaptive classification rules in the sense of Rukhin [Ru1] are given. The results are applied to the problem of the selection of the best population. Exponential families are studied as a special case, and an example for the normal case is included.
LA - eng
KW - generating functions of likelihood ratio; exponential family; generating functions of likelihood ratio; exponential family
UR - http://eudml.org/doc/33430
ER -
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