NA样本下基于递推型核估计的概率密度函数的经验似然推断

Empirical Likelihood for Probability Density Functions Based on Recursive Estimators under NA Samples

摘要: 在NA样本下, 本文研究了基于递推型估计的概率密度函数的置信区间的构造, 证明了分块经验似然比统计量的极限分布为chi^2分布, 并利用此结果构造了概率密度函数的经验似然置信区间.

Abstract: In this paper, we study the construction of confidence intervals for a probability density function under a negatively associated (NA) sample based on recursive estimators. It is shown that the blockwise empirical likelihood (EL) ratio statistic is asymptotically chi^2-type distributed, which is used to obtain EL-based confidence interval for the probability density function.