• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of applied statistics >On the Bayesian analysis of the mixture of power function distribution using the complete and the censored sample
【24h】

On the Bayesian analysis of the mixture of power function distribution using the complete and the censored sample

机译：关于使用完备样本和删失样本的幂函数分布混合的贝叶斯分析

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The power function distribution is often used to study the electrical component reliability. In this paper, we model a heterogeneous population using the two-component mixture of the power function distribution. A comprehensive simulation scheme including a large number of parameter points is followed to highlight the properties and behavior of the estimates in terms of sample size, censoring rate, parameters size and the proportion of the components of the mixture. The parameters of the power function mixture are estimated and compared using the Bayes estimates. A simulated mixture data with censored observations is generated by probabilistic mixing for the computational purposes. Elegant closed form expressions for the Bayes estimators and their variances are derived for the censored sample as well as for the complete sample. Some interesting comparison and properties of the estimates are observed and presented. The system of three non-linear equations, required to be solved iteratively for the computations of maximum likelihood (ML) estimates, is derived. The complete sample expressions for the ML estimates and for their variances are also given. The components of the information matrix are constructed as well. Uninformative as well as informative priors are assumed for the derivation of the Bayes estimators. A real-life mixture data example has also been discussed. The posterior predictive distribution with the informative Gamma prior is derived, and the equations required to find the lower and upper limits of the predictive intervals are constructed. The Bayes estimates are evaluated under the squared error loss function.
机译：功率函数分布通常用于研究电气组件的可靠性。在本文中，我们使用幂函数分布的两成分混合模型对异质总体进行建模。遵循包括大量参数点的综合模拟方案，以根据样本大小，检查率，参数大小和混合物成分的比例来突出估计的属性和行为。使用贝叶斯估计来估计和比较幂函数混合的参数。出于计算目的，通过概率混合生成带有审查观测值的模拟混合物数据。贝叶斯估计量及其方差的优雅闭合形式表达式是针对被检样本以及整个样本得出的。观察并给出了一些有趣的比较和估计的性质。推导了三个非线性方程组，它们需要迭代求解才能计算出最大似然（ML）估计值。还给出了ML估计及其方差的完整样本表达式。信息矩阵的组成部分也被构造。对于贝叶斯估计量的推导，假定无先验信息和先验信息。还讨论了现实生活中的混合物数据示例。得出具有信息Gamma先验的后验预测分布，并构建了找到预测区间上下限所需的方程。在平方误差损失函数下评估贝叶斯估计。

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