EM algorithm for mixture distributions model with type-I hybrid censoring scheme

淡江大學機構典藏 > 商管學院 > 統計學系暨研究所 > 期刊論文 > Item 987654321/122521

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题名:	EM algorithm for mixture distributions model with type-I hybrid censoring scheme
作者:	Tzong-Rr Tsai;Y. Lio;W-C Ting
关键词:	bootstrap method;EM algorithm;maximum likelihood estimation;mixture distributions model;Monte Carlo simulation
日期:	2021-10-04
上传时间:	2022-03-11 12:12:34 (UTC+8)
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.
關聯:	Mathematics 9(19), 2483
DOI:	10.3390/math9192483
显示于类别:	[統計學系暨研究所] 期刊論文

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