当前位置:
X-MOL 学术
›
Fluct. Noise Lett.
›
论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Estimation of the Parameters of Generalized Inverse Weibull Geometric Distribution and its Application
Fluctuation and Noise Letters ( IF 1.8 ) Pub Date : 2021-02-28 , DOI: 10.1142/s0219477521500437 Parviz Nasiri 1 , Amir Abbas Azarian 2
Fluctuation and Noise Letters ( IF 1.8 ) Pub Date : 2021-02-28 , DOI: 10.1142/s0219477521500437 Parviz Nasiri 1 , Amir Abbas Azarian 2
Affiliation
Inverse Weibull distribution is one of the distributions having a wide use for modeling system reliability and survival analysis. Recently, some of the researchers have compounded these distributions with some others to improve their models. In this paper, we present the compounded generalized inverse Weibull with geometric distribution. To estimate the parameters, we discuss the maximum likelihood using EM algorithm and Bayesian estimation for compound parameter of distribution. Efficacy of estimators using EM algorithm and minimum distance method is compared using mean square error. Finally, this distribution is fitted to a real dataset.
中文翻译:
广义逆Weibull几何分布参数的估计及其应用
逆 Weibull 分布是广泛用于建模系统可靠性和生存分析的分布之一。最近,一些研究人员将这些分布与其他一些分布相结合,以改进他们的模型。在本文中,我们提出了具有几何分布的复合广义逆 Weibull。为了估计参数,我们讨论了使用 EM 算法和贝叶斯估计的复合分布参数的最大似然。使用均方误差比较使用 EM 算法和最小距离法的估计器的有效性。最后,将此分布拟合到真实数据集。
更新日期:2021-02-28
中文翻译:
广义逆Weibull几何分布参数的估计及其应用
逆 Weibull 分布是广泛用于建模系统可靠性和生存分析的分布之一。最近,一些研究人员将这些分布与其他一些分布相结合,以改进他们的模型。在本文中,我们提出了具有几何分布的复合广义逆 Weibull。为了估计参数,我们讨论了使用 EM 算法和贝叶斯估计的复合分布参数的最大似然。使用均方误差比较使用 EM 算法和最小距离法的估计器的有效性。最后,将此分布拟合到真实数据集。