Posterior regret Γ-minimax estimation in a normal model with asymmetric loss function

Agata Boratyńska

Applicationes Mathematicae (2002)

  • Volume: 29, Issue: 1, page 7-13
  • ISSN: 1233-7234

Abstract

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The problem of posterior regret Γ-minimax estimation under LINEX loss function is considered. A general form of posterior regret Γ-minimax estimators is presented and it is applied to a normal model with two classes of priors. A situation when the posterior regret Γ-minimax estimator, the most stable estimator and the conditional Γ-minimax estimator coincide is presented.

How to cite

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Agata Boratyńska. "Posterior regret Γ-minimax estimation in a normal model with asymmetric loss function." Applicationes Mathematicae 29.1 (2002): 7-13. <http://eudml.org/doc/279123>.

@article{AgataBoratyńska2002,
abstract = {The problem of posterior regret Γ-minimax estimation under LINEX loss function is considered. A general form of posterior regret Γ-minimax estimators is presented and it is applied to a normal model with two classes of priors. A situation when the posterior regret Γ-minimax estimator, the most stable estimator and the conditional Γ-minimax estimator coincide is presented.},
author = {Agata Boratyńska},
journal = {Applicationes Mathematicae},
keywords = {Bayes estimators; classes of priors; robust Bayes estimation; posterior regret -minimax estimation; LINEX loss},
language = {eng},
number = {1},
pages = {7-13},
title = {Posterior regret Γ-minimax estimation in a normal model with asymmetric loss function},
url = {http://eudml.org/doc/279123},
volume = {29},
year = {2002},
}

TY - JOUR
AU - Agata Boratyńska
TI - Posterior regret Γ-minimax estimation in a normal model with asymmetric loss function
JO - Applicationes Mathematicae
PY - 2002
VL - 29
IS - 1
SP - 7
EP - 13
AB - The problem of posterior regret Γ-minimax estimation under LINEX loss function is considered. A general form of posterior regret Γ-minimax estimators is presented and it is applied to a normal model with two classes of priors. A situation when the posterior regret Γ-minimax estimator, the most stable estimator and the conditional Γ-minimax estimator coincide is presented.
LA - eng
KW - Bayes estimators; classes of priors; robust Bayes estimation; posterior regret -minimax estimation; LINEX loss
UR - http://eudml.org/doc/279123
ER -

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