出版日期：2021-06-01 00:00:00

著者：Xi Zheng; Jyun-You Chiang; Tzong-Ru Tsai; Shuai Wanga

著錄名稱、卷期、頁數：Computers & Industrial Engineering 156, 107188

摘要：The Log-logistic distribution has successfully earned attention in practical applications due to its good statistical properties. Because the traditional maximum likelihood estimators of the Log-logistic distribution parameters do not have an explicit form and are biased when the sample size is small. Therefore, the estimation and prediction of the failure rate is not well. In this study, we study the quality of the maximum likelihood, asymptotic maximum likelihood and bias-corrected maximum likelihood methods, and propose a smooth adaptive estimation method for estimating the Log-logistic distribution parameters. To reduce the bias of the asymptotic maximum likelihood and smooth adaptive estimators of the Log-logistic distribution parameters, the bias-corrected method is used to improve the asymptotic maximum likelihood and smooth adaptive estimation methods. Two new bias-corrected estimation methods are also proposed to obtain reliable estimates of the Log-logistic distribution parameters. An intensive Monte Carlo simulation study is conducted to evaluate the performance of these estimation methods. Simulation results show that the smooth adaptive and two new bias-corrected estimation methods are more competitive than other competitors. Finally, two real example is used for illustrating the applications of the smooth adaptive, CAML and CSA estimation methods.

關鍵字：Log-logistic distribution;Smooth adaptive method;Failure rate;Bias reduction;Maximum likelihood estimation

語言：en_US

ISSN：0360-8352

期刊性質：國外

收錄於：SCI Scopus

審稿制度：是

國別：GBR

出版型式：電子版