摘要
对于在附加信息Eg（X）＝0下，用经验似然方法所获得的分布函数和分位数估计，给出了这些估计的强相合性，渐近正态性和重对数律，并且说明它们的渐近方差比通常分布函数和分位数估计的渐近方差要小。
The strong consistency, asmptotic normality and the law of the iterated logarithm are obtained for the distribution function and quantile esthates derived by the empirical likelihood method in the presence of auxiliary Eg(X)=0. Moreover, their asymptotic variances are smaller than that of classical distribution and quantile estimates respectively.
出处
《北京师范大学学报（自然科学版）》
CAS
CSCD
北大核心
1998年第4期450-455,共6页
Journal of Beijing Normal University(Natural Science)
基金
国家自然科学基金!19771011
北京师范大学基金
关键词
附加信息
分位数估计
分布函数
渐近性质
empirical likelihood ratio
auxiliary information
the law of the iterated logarithm
quantile estimate
