出版日期：2022-11-05 00:00:00

著者：Tzong-Ru Tsai; Hua Xin; Ya-Yen Fan; Yuhlong Lio

著錄名稱、卷期、頁數：Stats 5(4), p.1079-1096

摘要：In this study, the estimation methods of bias-corrected maximum likelihood (BCML), bootstrap BCML (B-BCML) and Bayesian using Jeffrey’s prior distribution were proposed for the inverse Gaussian distribution with small sample cases to obtain the ML and Bayes estimators of the model parameters and the process performance index based on the lower specification process performance index. Moreover, an approximate confidence interval and the highest posterior density interval of the process performance index were established via the delta and Bayesian inference methods, respectively. To overcome the computational difficulty of sampling from the posterior distribution in Bayesian inference, the Markov chain Monte Carlo approach was used to implement the proposed Bayesian inference procedures. Monte Carlo simulations were conducted to evaluate the performance of the proposed BCML, B-BCML and Bayesian estimation methods. An example of the active repair times for an airborne communication transceiver is used for illustration.

關鍵字：Bayesian estimation;bootstrap method;maximum likelihood estimation;process capability analysis;process performance index

語言：en

ISSN：2571-905X

期刊性質：國外

收錄於：ESCI

審稿制度：是

國別：CHE

出版型式：電子版