The admissibility of the empirical distribution function

DOI10.1214/aos/1176346591zbMath0575.62011OpenAlexW2041609350MaRDI QIDQ1063964

Michael P. Cohen, Lynn Kuo

Publication date: 1985

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1176346591

zbMATH Keywords

multinomial distributionempirical distributionsimple random sampling without replacementsimultaneous estimationfinite population samplingmultivariate hypergeometric distributionweighted quadratic loss

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Sampling theory, sample surveys (62D05) Order statistics; empirical distribution functions (62G30) Admissibility in statistical decision theory (62C15)

Related Items (12)

Some Bayesian Methods for Two Auditing Problems ⋮ Minimax estimation of a variance ⋮ On continuous distribution functions, minimax and best invariant estimators, and integrated balanced loss functions ⋮ A general method of finding a minimax estimator of a distribution function when no equalizer rule is available ⋮ Methodology for the invariant estimation of a continuous distribution function ⋮ Minimaxity and admissibility of the product limit estimator ⋮ Minimum Risk Invariant Estimators of a Continuous Cumulative Distribution Function ⋮ Minimax invariant estimator of a continuous distribution function ⋮ Minimax estimation of a cumulative distribution function by converting to a parametric problem ⋮ On extended admissible procedures and their nonstandard Bayes risk ⋮ Minimax Prediction of the Empirical Distribution Function ⋮ Admissibility of the empirical distribution function in discrete nonparametric invariant problems

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