Bayesian Estimation and Prediction Using Asymmetric Loss Functions
- 1 June 1986
- journal article
- research article
- Published by JSTOR in Journal of the American Statistical Association
- Vol. 81 (394) , 446
- https://doi.org/10.2307/2289234
Abstract
Estimators and predictors that are optimal relative to Varian's asymmetric LINEX loss function are derived for a number of well-known models. Their risk functions and Bayes risks are derived and compared with those of usual estimators and predictors. It is shown that some usual estimators, for example, a scalar sample mean or a scalar least squares regression coefficient estimator, are inadmissible relative to asymmetric LINEX loss by providing alternative estimators that dominate them uniformly in terms of risk.Keywords
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