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臺灣學術機構典藏系統 (Taiwan Academic Institutional Repository, TAIR)
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Institution Date Title Author
淡江大學 2025-06-14 Likelihood and pivotal inference for Kumaraswamy parameters under progressive type-II censoring Wu, Shuo-Jye;Tseng, Yao-Ting;Kus, Coskun
淡江大學 2025-03-20T01:31:14Z Analysis of block adaptive type-II progressive hybrid censoring with Weibull distribution Singh, Kundan;Tripathi, Yogesh Mani;Wang, Liang;Wu, Shuo-Jye
淡江大學 2025-03-20T01:31:11Z Estimation and prediction of modified progressive hybrid censored data from inverted exponentiated Rayleigh distribution Wang, Liang;Wu, Shuo-Jye;Tripathi, Yogesh Mani;Dey, Sanku
淡江大學 2025-02-28 Bayesian inference and optimal plan for the family of inverted exponentiated distribution under doubly censored data Gupta, Chandan Kumar;Chandra, Prakash;Tripathi, Yogesh Mani;Wu, Shuo-jye
淡江大學 2024-12-16 Analysis of block adaptive type-II progressive hybrid censoring with Weibull distribution Singh, Kundan;Tripathi, Yogesh Mani;Wang, Liang;Wu, Shuo-Jye
淡江大學 2024-08 Estimation for partially observed left truncation and right censored competing risks data from a generalized inverted exponential distribution with illustrations Wang, Liang;Zhang, Chunfang;Wu, Shuo-Jye;Dey, Sanku;Lioe, Yuhlong
淡江大學 2024-08 Estimation and prediction of modified progressive hybrid censored data from inverted exponentiated Rayleigh distribution Wang, Liang;Wu, Shuo-Jye;Tripathi, Yogesh Mani;Dey, Sanku
淡江大學 2024-08 Estimation for partially observed left truncation and right censored competing risks data from a generalized inverted exponential distribution with illustrations Wang, Liang;Zhang, Chunfang;Wu, Shuo-Jye;Dey, Sanku;Lioe, Yuhlong
淡江大學 2023-06-07 Estimation and prediction of modified progressive hybrid censored data from inverted exponentiated Rayleigh distribution Wu, Shuo-jye
淡江大學 2023-06-05 Estimation for partially observed left truncation and right censored competing risks data from a generalized inverted exponential distribution with illustrations Wu, Shuo-jye

Showing items 1-10 of 73  (8 Page(s) Totally)
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