Parameter Estimation of the Burr Type XII Distribution with a Progressively Interval-censored Scheme Using Genetic Algorithm
學年 103
學期 2
發表日期 2015-03-28
作品名稱 Parameter Estimation of the Burr Type XII Distribution with a Progressively Interval-censored Scheme Using Genetic Algorithm
作品名稱（其他語言）
著者 Tsai, Tzong-Ru; Jiang, Jyun-You; Lio, Yuhlong; Jiang, Nan; Fan, Ya-Yen
作品所屬單位 淡江大學統計學系
出版者
會議名稱 The 3rd International Conference on Industrial Application Engineering 2015
會議地點 Kitakyushu, Japan
摘要 Burr type XII distribution (BXIID) has been widely used to model lifetime data sets. The flexibility of the BXIID is established due to its two shape parameters. To save test time and cost, the BXIID parameters can be inferred by using the maximum likelihood estimation method based on a date set with incomplete lifetime information. But the maximum likelihood estimates (MLEs) of BXIID parameters could have a big bias and mean squared error (MSE) if the sample size is small or the MLEs are evaluated with improper initial parameters. In this study, a progressively interval-censored (PIC) scheme is used to implement the life test, and the Genetic Algorithm (GA) is applied to reduce the bias and MSEs of the MLEs of the BXIID parameters. An extensive Monte Carlo simulation was conducted to evaluate the estimation performance of the typical maximum likelihood estimation method (TMLEM) and GA. Simulation results show that the GA is competitive with the TMLEM in terms of resulting in a smaller bias and MSE in parameter estimation.
關鍵字 Burr type XII distribution; Genetic Algorithm;
 maximum likelihood estimation; Monte Carlo
 simulation; progressively interval-censored scheme
語言 en
收錄於
會議性質 國際
校內研討會地點
研討會時間 20150328~20150331
通訊作者 Tsai, Tzong-Ru
國別 JPN
公開徵稿
出版型式 電子版
出處 Proceeding of the 3rd International Conference on Industrial Application Engineering 2015
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