Statistical analysis of Extreme-value and Pareto distributed data under Type II progressive censoring with binomial and random removals

• Main Authors: Huang -Yu Chan, 詹煌宇
• Other Authors: Chin-Chuan Wu
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/20869733130148881386

碩士 === 淡江大學 === 統計學系 === 90 === Studies in the lifetimes of the organisms and products are often the main research topics in the nature and industries. The past research developed some censored methods. Before the experiments did not end yet, some patients might not proceed the experiments due to some factors. Furthermore, the experiments were ended early because some experimenters might be hazardous for the experiments during the experiments or not tally with the demands of the experiments. In order to resolve these problems, progressive removal was developed. This thesis mainly concentrates on the statistical analysis of Extreme-value distributed and Pareto distributed lifetime data under Type II progressive censoring with binomial and random removals. To begin with, the thesis discusses the maximum likelihood estimates and characteristics of the parameters in the distributions. We respectively narrate binomial and random removals. Then, we separately deduce the expected values of Extreme-value distribution and Pareto distribution under binomial and random removals. Adjusting the parameter values of the distributions counts up to the expected time. Finally, we farther analyze the expected time of Extreme-value distribution and Pareto distribution under Type II progressive censoring with binomial and random removals.