首页> 外文期刊>Journal of applied statistics >Comparison between method of moments and entropy regularization algorithm applied to parameter estimation for mixed-Weibull distribution
【24h】

Comparison between method of moments and entropy regularization algorithm applied to parameter estimation for mixed-Weibull distribution

机译:混合Weibull分布参数估计中矩方法与熵正则化算法的比较

获取原文
获取原文并翻译 | 示例
       

摘要

Mixed-Weibull distribution has been used to model a wide range of failure data sets, and in many practical situations the number of components in a mixture model is unknown. Thus, the parameter estimation of a mixed-Weibull distribution is considered and the important issue of how to determine the number of components is discussed. Two approaches are proposed to solve this problem. One is the method of moments and the other is a regularization type of fuzzy clustering algorithm. Finally, numerical examples and two real data sets are given to illustrate the features of the proposed approaches.
机译:混合威布尔分布已用于对各种故障数据集进行建模,并且在许多实际情况下,未知混合模型中的组件数量。因此,考虑了混合威布尔分布的参数估计,并讨论了如何确定分量数的重要问题。提出了两种方法来解决这个问题。一种是矩量法,另一种是正则化类型的模糊聚类算法。最后,通过数值算例和两个实际数据集来说明所提出方法的特征。

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