Journal of the American Statistical Association · 1986 · 206 citations · 0 references
BusinessDecision SciencesBayesian Data AnalysisRisk AnalysisStatistical ModelingBayesian InferenceBayesian StatisticsLoss FunctionRisk EstimationRisk ModelingRisk Of LossBayes EstimationBayes RiskBayesian EstimationBayesian Loss ModelingBayesian Risk AnalysisBayesian Risk EstimationLeast Squares EstimationProbabilistic Loss Modeling
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. Key Words: Asymmetric loss functionInadmissibilityEstimationPredictionRisk functionRobustness