A general method of finding a minimax estimator of a distribution function when no equalizer rule is available

DOI10.2307/3315315zbMath0755.62018OpenAlexW2160544836MaRDI QIDQ4024615

Qi Qing Yu

Publication date: 4 February 1993

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3315315

zbMATH Keywords

order statisticsminimax estimatorsempirical distributionNP problemequalizer ruleminimax binomial parametric problems

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Minimax procedures in statistical decision theory (62C20)

Related Items (4)

Minimax estimation of a bivariate cumulative distribution function ⋮ Minimum Risk Invariant Estimators of a Continuous Cumulative Distribution Function ⋮ Minimax estimation of a cumulative distribution function by converting to a parametric problem ⋮ Minimax Prediction of the Empirical Distribution Function

Cites Work

• The admissibility of the empirical distribution function
• Minimaxity of the empirical distribution function in invariant estimation
• Minimaxity and admissibility of the product limit estimator
• Admissibility in discrete and continuous invariant nonparametric estimation problems and in their multinomial analogs
• Minimax estimation of a cumulative distribution function
• The Theory of Decision Procedures for Distributions with Monotone Likelihood Ratio
• Asymptotic Minimax Character of the Sample Distribution Function and of the Classical Multinomial Estimator
• On the Admissible Estimators for Certain Fixed Sample Binomial Problems
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