期刊論文

學年 110
學期 2
出版(發表)日期 2022-03-17
作品名稱 Bias correction method for log-power-normal distribution
作品名稱(其他語言)
著者 Tzong-Ru Tsai; Yuhlong Lio; Ya-Yen Fan; Che-Pin Cheng
單位
出版者
著錄名稱、卷期、頁數 Mathematics 10(6), 955
摘要 The log-power-normal distribution is a generalized version of the log-normal distribution. The maximum likelihood estimation method is the most popular method to obtain the estimates of the log-power-normal distribution parameters. In this article, we investigate the performance of the maximum likelihood estimation method for point and interval inferences. Moreover, a simple method that has less impact from the subjective selection of the initial solutions to the model parameters is proposed. The bootstrap bias correction method is used to enhance the estimation performance of the maximum likelihood estimation method. The proposed bias correction method is simple for use. Monte Carlo simulations are conducted to check the quality of the proposed bias correction method. The simulation results indicate that the proposed bias correction method can improve the performance of the maximum likelihood estimation method with a smaller bias and provide a coverage probability close to the nominal confidence coefficient. Two real examples about the air pollution and cement’s concrete strength are used for illustration.
關鍵字 bias correction;log-power-normal distribution;maximum likelihood estimation;Monte Carlo simulation;quality control
語言 en
ISSN 2227-7390
期刊性質 國外
收錄於 SCI Scopus
產學合作
通訊作者
審稿制度
國別 CHE
公開徵稿
出版型式 ,電子版