{"title":"基于I型截尾数据的logistic分布拟合优度检验","authors":"Samah Ahmed, A. Baklizi, Reza Pakyari","doi":"10.37119/jpss2023.v21i1.663","DOIUrl":null,"url":null,"abstract":"A goodness of fit test procedure is proposed for the log-logistic distribution when the available data are subject to Type I censoring. The proposed test is based on transforming type 1 censored data into complete data from a suitably truncated distribution. A Monte Carlo power study is conducted to evaluate and compare the performance of the proposed method with the existing classical methods. An application based on a real dataset is considered for illustrative purposes","PeriodicalId":161562,"journal":{"name":"Journal of Probability and Statistical Science","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Goodness of Fit Testing for the Log-logistic Distribution Based on Type I Censored Data\",\"authors\":\"Samah Ahmed, A. Baklizi, Reza Pakyari\",\"doi\":\"10.37119/jpss2023.v21i1.663\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A goodness of fit test procedure is proposed for the log-logistic distribution when the available data are subject to Type I censoring. The proposed test is based on transforming type 1 censored data into complete data from a suitably truncated distribution. A Monte Carlo power study is conducted to evaluate and compare the performance of the proposed method with the existing classical methods. An application based on a real dataset is considered for illustrative purposes\",\"PeriodicalId\":161562,\"journal\":{\"name\":\"Journal of Probability and Statistical Science\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Probability and Statistical Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37119/jpss2023.v21i1.663\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Probability and Statistical Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37119/jpss2023.v21i1.663","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Goodness of Fit Testing for the Log-logistic Distribution Based on Type I Censored Data
A goodness of fit test procedure is proposed for the log-logistic distribution when the available data are subject to Type I censoring. The proposed test is based on transforming type 1 censored data into complete data from a suitably truncated distribution. A Monte Carlo power study is conducted to evaluate and compare the performance of the proposed method with the existing classical methods. An application based on a real dataset is considered for illustrative purposes
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
