On continuous distribution functions, minimax and best invariant estimators, and integrated balanced loss functions
Author:
Affiliation:
1. University of Manitoba, Department of Statistics; Winnipeg MB, Canada R3T 2N2
2. Université de Sherbrooke, Département de mathématiques; Sherbrooke QC, Canada J1K 2R1
Funder
Natural Sciences and Engineering Research Council of Canada
Publisher
Wiley
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
http://onlinelibrary.wiley.com/wol1/doi/10.1002/cjs.11217/fullpdf
Reference30 articles.
1. Some minimax invariant procedures for estimating a cumulative distribution function;Aggarwal;The Annals of Mathematical Statistics,1955
2. Estimating a distribution function based on nomination sampling;Boyles;Journal of the American Statistical Association,1986
3. A complete class theorem for strict monotone likelihood ratio with applications;Brown;Annals of Statistics,1976
4. Admissibility in discrete and continuous invariant nonparametric estimation problems and in their multinomial analogs;Brown;Annals of Statistics,1988
5. The admissibility of the empirical distribution function;Cohen;Annals of Statistics,1985
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