首页> 外文期刊>Journal of nonparametric statistics >Efficient algorithms for computing the non and semi-parametric maximum likelihood estimates with panel count data
【24h】

Efficient algorithms for computing the non and semi-parametric maximum likelihood estimates with panel count data

机译:利用面板计数数据计算非和半参数最大似然估计的高效算法

获取原文
获取原文并翻译 | 示例
           

摘要

Nonparametric and semi-parametric analysis of panel count data have recently been active research topics in statistical literature. The maximum likelihood method based on the non-homogeneous Poisson process has been proved an efficient inference procedure for such analysis. However, computing the non- and semi-parametric maximum likelihood estimates (MLEs) can be very intensive numerically and the available methods are not efficient. In this manuscript, we develop an efficient numerical algorithm stemming from the Newton-Raphson method to compute the non- and semi-parametric MLEs for panel count data. Simulation studies are carried out to demonstrate the numerical efficiency of the proposed algorithm compared to the existing methods in the literature.
机译:面板计数数据的非参数和半参数分析最近已成为统计文献中的活跃研究主题。基于非均匀泊松过程的最大似然方法已被证明是一种有效的推理程序。但是,计算非参数和半参数最大似然估计(MLE)可能在数字上非常密集,并且可用的方法效率不高。在本手稿中,我们开发了一种有效的数值算法,其源于Newton-Raphson方法,用于计算面板计数数据的非参数和半参数MLE。仿真研究表明,与文献中的现有方法相比,该算法的数值效率更高。

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