出版日期：2022-08-04 00:00:00

著者：Tzong-Ru Tsai; H Xin; Ya-Yen Fan; YL Lio

會議名稱：27th ISSAT International Conference on Reliability and Quality in Design

會議地點：線上

摘要：An analytical bias-corrected maximum likelihood estimation procedure and a bootstrap bias-corrected maximum likelihood estimation procedure are proposed for the inverse Gaussian distribution (IGD) to obtain more reliable maximum likelihood estimates (MLEs) of the model parameters and the generalized process capability index (PCI) proposed by Maiti et al. (2010) when the sample size is small. An approximate confidence interval (ACI) of the generalized PCI is obtained for the IGD via using the delta method and the obtained reliable MLEs of the model parameters. Monte Carlo simulations were conducted to evaluate the performance of two proposed estimation methods. Simulation results show that two proposed bias-correction methods outperform the typical maximum likelihood estimation method when the sample size is small in terms of the relative bias and relative mean squared error. © 2022 International Society of Science and Applied Technologies

關鍵字：Bias correction;bootstrap methods;Fisher information matrix;inverse Gaussian distribution;maximum likelihood estimation

語言：en_US

會議性質：國際

校內研討會地點：無

研討會時間：20220804~20220806

國別：USA

出處：27th ISSAT International Conference on Reliability and Quality in Design, p.86-90