On Characterization of Second-Order Asymptotic Optimality Under Asymmetric Loss Functions: Loss Coefficient Vector and Admissibility

DOI10.1080/03610920802376348zbMath1318.62022OpenAlexW2008541359MaRDI QIDQ3585243

Yoshiji Takagi

Publication date: 19 August 2010

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920802376348

zbMATH Keywords

second-order admissibilityasymmetric loss functionsloss coefficient vector

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Bayesian problems; characterization of Bayes procedures (62C10) Admissibility in statistical decision theory (62C15)

Cites Work

• Unnamed Item
• Statistical decision theory. Foundations, concepts, and methods
• A necessary and sufficient condition for second order admissibility with applications to Berkson's bioassay problem
• Defining the curvature of a statistical problem (with applications to second order efficiency)
• Local asymptotic minimax risk bounds for asymmetric loss functions
• SECOND ORDER ASYMPTOTIC COMPARISON OF ESTIMATORS UNDER UNIVERSAL DOMINATION CRITERION
• Bayesian Estimation and Prediction Using Asymmetric Loss Functions

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