负相协样本多维边际密度的经验似然推断

Empirical Likelihood for Marginal Joint Probability Density Functions of a Negatively Associated Sample

研究负相协样本多维边际密度函数的经验似然置信区间的构造,证明了负相协样本多维边际密度函数的分组经验似然比统计量的极限分布为卡方分布,由此结果可构造多维边际密度函数的经验似然置信区间。

This paper studies the construction of confidence intervals for the marginal joint probability density functions of a negatively associated（NA） sample by are studied using the blockwise technique.It is shows that the blockwise empirical likelihood（EL） ratio statistic is asymptotically χ2-type distributed,which is used to obtain EL-based confidence interval for the probability density functions.