首页> 外文期刊>Journal of nonparametric statistics >Level-specific correction for nonparametric likelihoods
【24h】

Level-specific correction for nonparametric likelihoods

机译:针对非参数可能性的特定级别校正

获取原文
获取原文并翻译 | 示例
       

摘要

The popular empirical likelihood method not only has a convenient chi-square limiting distribution but is also Bartlett correctable, leading to a high-order coverage precision of the resulting confidence regions. Meanwhile, it is one of many nonparametric likelihoods in the Cressie-Read power divergence family. The other likelihoods share many attractive properties but are not Bartlett correctable. In this paper, we develop a new technique to achieve the effect of being Bartlett correctable. Our technique is generally applicable to pivotal quantities with chi-square limiting distributions. Numerical experiments and an example reveal that the method is successful for several important nonparametric likelihoods.
机译:流行的经验似然方法不仅具有便利的卡方限度分布,而且还可以进行巴特利特校正,从而导致所得置信区域的高阶覆盖精度。同时,它是Cressie-Read功率散度族中许多非参数可能性之一。其他可能性具有许多吸引人的特性,但Bartlett不可校正。在本文中,我们开发了一种新技术来实现Bartlett可校正的效果。我们的技术通常适用于具有卡方限制分布的枢轴数量。数值实验和算例表明,该方法对几种重要的非参数似然法是成功的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号