矩条件下模型估计与检验的分歧与对偶
Divergences and Duality for Estimation and Test under Moment Condition Models
摘要：
我们介绍了通过散度最小化模型满足线性约束与未知参数的估计和测试程序。这些程序扩展了经验似然（EL）方法，并与广义经验似然方法具有共同的特征。本文讨论了符号有限测度集上概率分布的发散投影的存在性和特征。我们给出了这类估计和检验统计量的对偶性的一个精确刻画，并利用它在零假设和替换或误设下导出了它们的极限分布（包括EL估计和EL比统计量）.推导出幂函数的近似值以及样本量，以确保给定替代方案的所需功效。
英文摘要：
We introduce estimation and test procedures through divergence minimiza- tion for models satisfying linear constraints with unknown parameter. These procedures extend the empirical likelihood (EL) method and share common features with generalized empirical likelihood approach. We treat the problems of existence and characterization of the divergence projections of probability distributions on sets of signed finite measures. We give a precise characterization of duality, for the proposed class of estimates and test statistics, which is used to derive their limiting distributions (including the EL estimate and the EL ratio statistic) both under the null hypotheses and under alterna- tives or misspecification. An approximation to the power function is deduced as well as the sample size which ensures a desired power for a given alternative.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
