Methodology for the invariant estimation of a continuous distribution function

DOI10.1007/BF00050665zbMath0698.62037MaRDI QIDQ912524

Qi Qing Yu

Publication date: 1989

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

zbMATH Keywords

Lebesgue measuredistribution estimationbest invariant estimatorweighted quadratic lossApproximation of estimatorsclass of invariant estimatorsfinite sample problemminimaxity of estimatorsnonrandomized estimator

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Minimax procedures in statistical decision theory (62C20) Admissibility in statistical decision theory (62C15)

Related Items (3)

On continuous distribution functions, minimax and best invariant estimators, and integrated balanced loss functions ⋮ Minimum Risk Invariant Estimators of a Continuous Cumulative Distribution Function ⋮ Minimax invariant estimator of a continuous distribution function

Cites Work

• Unnamed Item
• Inadmissibility of the empirical distribution function in continuous invariant problems
• The admissibility of the empirical distribution function
• Admissibility in discrete and continuous invariant nonparametric estimation problems and in their multinomial analogs
• Minimax estimation of a cumulative distribution function
• Asymptotic Minimax Character of the Sample Distribution Function and of the Classical Multinomial Estimator
• The Asymptotic Inadmissibility of the Sample Distribution Function
• Some Minimax Invariant Procedures for Estimating a Cumulative Distribution Function

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