The Hájek convolution theorem and empirical Bayes estimation: Parametrics, semiparametrics and nonparametrics

DOI10.1016/S0378-3758(00)00198-1zbMath0965.62004OpenAlexW2082501590MaRDI QIDQ5928951

Pranab Kumar Sen

Publication date: 31 July 2001

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-3758(00)00198-1

zbMATH Keywords

robustnessadaptive estimatorasymptotic (first-order) representationBayes factorgeneralized Pitman-closenessquadratic riskStein-rule estimatorsZellner's g-prior

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric estimation (62G05) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (2)

Pitman closeness of sample median to population median ⋮ Contiguity and irreconcilable nonstandard asymptotics of statistical tests

Cites Work

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• Nonparametric empirical bayes estimation of certain funtionals
• A james-stein type detour of U-statistics
• On sequentially adaptive signed-rank statistics
• A characterization of limiting distributions of regular estimates
• A Class of Statistics with Asymptotically Normal Distribution
• On the Asymptotic Distribution of Differentiable Statistical Functions

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