出版日期：2021-10-04 00:00:00

著者：Tzong-Rr Tsai; Y. Lio; W-C Ting

著錄名稱、卷期、頁數：Mathematics 9(19), 2483

摘要：An expectation–maximization (EM) likelihood estimation procedure is proposed to obtain the maximum likelihood estimates of the parameters in a mixture distributions model based on type-I hybrid censored samples when the mixture proportions are unknown. Three bootstrap methods are applied to construct the confidence intervals of the model parameters. Monte Carlo simulations are conducted to evaluate the performance of the proposed methods. Simulation results show that the proposed methods can perform well to obtain reliable point and interval estimation results. Three examples are used to illustrate the applications of the proposed methods.

關鍵字：bootstrap method;EM algorithm;maximum likelihood estimation;mixture distributions model;Monte Carlo simulation

語言：en_US

ISSN：2227-7390

期刊性質：國外

收錄於：SCI

審稿制度：是

國別：CHE

出版型式：電子版