强混合样本且含附加信息情形M估计和分位数估计的渐近性质

M-estimation and Quantile Estimation in the Presence of Auxiliary Information under Strong Mixing Sample

摘要: 在强混合样本且含附加信息情形,本文采用经验似然方法提出了一类新的~M~估计和新的分位数估计.结果表明, 本文提出的~M~估计和分位数估计具有相合性和渐近正态性,且其渐近方差比一般~M~估计和分位数估计的渐近方差小.

Abstract: In this paper, we apply the empirical likelihood technique to propose a new class of M-estimators and quantile estimators in the presence of some auxiliary information under strong mixing samples. It is shown that the proposed M-estimators and quantile estimators are consistent and asymptotically normally distributed with smaller asymptotic variances than those of the usual M-estimators and quantile estimators.