{"title":"基于ii型截尾样本的半logistic分布熵的贝叶斯估计","authors":"J. Seo, Suk-Bok Kang","doi":"10.3390/ECEA-1-B003","DOIUrl":null,"url":null,"abstract":"This paper provides statistical inferences on the entropy of the half-logistic distribution when the data are Type-II censored. The maximum likelihood estimator of the entropy and corresponding approximate confidence interval are derived. For Bayesian inferences, an objective Bayesian estimation method is developed based on the Jeffreys prior. The proposed estimation methods are compared through Monte Carlo simulations for various Type-II censoring schemes. Finally, real data are analyzed for illustration purposes.","PeriodicalId":44573,"journal":{"name":"International Journal of Applied Mathematics & Statistics","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Bayesian Estimation of the Entropy of the Half-Logistic Distribution Based on Type-II Censored Samples\",\"authors\":\"J. Seo, Suk-Bok Kang\",\"doi\":\"10.3390/ECEA-1-B003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper provides statistical inferences on the entropy of the half-logistic distribution when the data are Type-II censored. The maximum likelihood estimator of the entropy and corresponding approximate confidence interval are derived. For Bayesian inferences, an objective Bayesian estimation method is developed based on the Jeffreys prior. The proposed estimation methods are compared through Monte Carlo simulations for various Type-II censoring schemes. Finally, real data are analyzed for illustration purposes.\",\"PeriodicalId\":44573,\"journal\":{\"name\":\"International Journal of Applied Mathematics & Statistics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2014-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Applied Mathematics & Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/ECEA-1-B003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Applied Mathematics & Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/ECEA-1-B003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Bayesian Estimation of the Entropy of the Half-Logistic Distribution Based on Type-II Censored Samples
This paper provides statistical inferences on the entropy of the half-logistic distribution when the data are Type-II censored. The maximum likelihood estimator of the entropy and corresponding approximate confidence interval are derived. For Bayesian inferences, an objective Bayesian estimation method is developed based on the Jeffreys prior. The proposed estimation methods are compared through Monte Carlo simulations for various Type-II censoring schemes. Finally, real data are analyzed for illustration purposes.
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