摘要
研究了观察数据被随机删失时,极大似然估计的局部渐近正态性与渐近极小极大有效性,建立了局部渐近正态成立的充分条件,并给出渐近极小极大风险的下界以及达到该下界的充分必要条件,证明了随机删失下参数极大似然估计的渐近极小极大有效性.
In this paper, we study the local asymptotic normality and asymptotic minimax validity of maximum likelihood estimators when observational data are randomly censored. Sufficient conditions for the existence of local asymptotic normality are established. The lower bound of asymptotic minimax risk and sufficient and necessary conditions for reaching the lower bound are given. The asymptotic minimax validity of parametric maximum likelihood estimators under random censorship is proved.
作者
康宏亮
KANG Hong-liang(College of Mathematics and Statistics,Northwest Normal University,Lanzhou 730070,China)
出处
《兰州文理学院学报（自然科学版）》
2019年第2期1-7,共7页
Journal of Lanzhou University of Arts and Science(Natural Sciences)
基金
国家自然科学基金(71261023)
关键词
局部渐近正态
渐近极小极大有效
极大似然估计
local asymptotic normality
asymptotic minimax validity
maximum likelihood estimation
