Parameter estimation for composite dynamical systems based on sequential order statistics from Burr type XII mixture distribution
學年 109
學期 2
出版（發表）日期 2021-04-08
作品名稱 Parameter estimation for composite dynamical systems based on sequential order statistics from Burr type XII mixture distribution
作品名稱（其他語言）
著者 Tzong-Ru Tsai;Yuhlong Lio;Hua Xin;Hoang Pham
單位
出版者
著錄名稱、卷期、頁數 Mathematics 9(8), 810
摘要 Considering the impact of the heterogeneous conditions of the mixture baseline distribution on the parameter estimation of a composite dynamical system (CDS), we propose an approach to infer the model parameters and baseline survival function of CDS using the maximum likelihood estimation and Bayesian estimation methods. The power-trend hazard rate function and Burr type XII mixture distribution as the baseline distribution are used to characterize the changes of the residual lifetime distribution of surviving components. The Markov chain Monte Carlo approach via using a new Metropolis–Hastings within the Gibbs sampling algorithm is proposed to overcome the computation complexity when obtaining the Bayes estimates of model parameters. A numerical example is generated from the proposed CDS to analyze the proposed procedure. Monte Carlo simulations are conducted to investigate the performance of the proposed methods, and results show that the proposed Bayesian estimation method outperforms the maximum likelihood estimation method to obtain reliable estimates of the model parameters and baseline survival function in terms of the bias and mean square error
關鍵字 composite dynamical systems;hazard rate;Markov chain Monte Carlo;mixture distribution;sequential order statistics
語言 en
ISSN
期刊性質 國外
收錄於 SCI Scopus
產學合作
通訊作者
審稿制度 是
國別 CHE
公開徵稿
出版型式 ,電子版
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機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/120863 )

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