Local asymptotic normality and asymptotical minimax efficiency of the MLE under random censorship

• Published in: Science China. Mathematics Vol. 43; no. 6; pp. 591 - 600
• Main Authors: Wang, Qihua, Jing, Bingyi
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer Nature B.V 01.06.2000; Department of Probability and Statistics, Peking University, Beijing 100871, China%Department of Mathematics, Hong Kong University of Science and Technology, Hong Kong, China
• Subjects: Asymptotic properties; Lower bounds; Maximum likelihood estimators; Minimax technique; Normality; maximum likelihood estimator random censorship; local asymptotic normality; asymptotic minimax efficiency
• ISSN: 1006-9283; 1674-7283; 1862-2763; 1869-1862
• DOI: 10.1007/BF02908770

Here we study the problems of local asymptotic normality of the parametric family of distributions and asymptotic minimax efficient estimators when the observations are subject to right censoring. Local asymptotic normality will be established under some mild regularity conditions. A lower bound for local asymptotic minimax risk is given with respect to a bowl-shaped loss function, and furthermore a necessary and sufficient condition is given in order to achieve this lower bound. Finally, we show that this lower bound can be attained by the maximum likelihood estimator in the censored case and hence it is local asymptotic minimax efficient.