Empirical Bayes rules and Gaussian processes

DOI10.1016/0378-3758(82)90005-2zbMath0499.62012OpenAlexW1999880330MaRDI QIDQ1171841

Theo Stijnen

Publication date: 1982

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

Full work available at URL: https://doi.org/10.1016/0378-3758(82)90005-2

zbMATH Keywords

kernel estimatorsGaussian processesconvergence ratesquared error lossempirical Bayes estimatorscontinuous one-parameter exponential familyconditional Bayes risk

Mathematics Subject Classification ID

Bayesian problems; characterization of Bayes procedures (62C10) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (1)

Robust empirical Bayes tests for continuous distributions

Cites Work

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• Rates of convergence in empirical Bayes estimation problems: Continuous case
• Monotone empirical Bayes tests for the continuous one-parameter exponential family
• Empirical Bayes estimation in Lebesgue-exponential families with rates near the best possible rate
• On some global measures of the deviations of density function estimates
• An approximation of partial sums of independent RV'-s, and the sample DF. I
• Maxima of stationary Gaussian processes

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