{"title":"基于序统计量的ii型指数对数- logistic分布的推论及应用","authors":"D. Kumar, Maneesh Kumar, S. Dey","doi":"10.2991/jsta.d.200825.002","DOIUrl":null,"url":null,"abstract":"In this paper, we first derive the exact explicit expressions for the single and product moments of order statistics from the typeII exponentiated log-logistic distribution, and then use these results to compute the means, variances, skewness and kurtosis of rth order statistics. Besides, best linear unbiased estimators (BLUEs) for the location and scale parameters for the type-II exponentiated log-logistic distribution with known shape parameters are studied. Finally, the results are illustrated with a real data set.","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Inferences for the Type-II Exponentiated Log-Logistic Distribution Based on Order Statistics with Application\",\"authors\":\"D. Kumar, Maneesh Kumar, S. Dey\",\"doi\":\"10.2991/jsta.d.200825.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we first derive the exact explicit expressions for the single and product moments of order statistics from the typeII exponentiated log-logistic distribution, and then use these results to compute the means, variances, skewness and kurtosis of rth order statistics. Besides, best linear unbiased estimators (BLUEs) for the location and scale parameters for the type-II exponentiated log-logistic distribution with known shape parameters are studied. Finally, the results are illustrated with a real data set.\",\"PeriodicalId\":45080,\"journal\":{\"name\":\"Journal of Statistical Theory and Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistical Theory and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/jsta.d.200825.002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistical Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/jsta.d.200825.002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
Inferences for the Type-II Exponentiated Log-Logistic Distribution Based on Order Statistics with Application
In this paper, we first derive the exact explicit expressions for the single and product moments of order statistics from the typeII exponentiated log-logistic distribution, and then use these results to compute the means, variances, skewness and kurtosis of rth order statistics. Besides, best linear unbiased estimators (BLUEs) for the location and scale parameters for the type-II exponentiated log-logistic distribution with known shape parameters are studied. Finally, the results are illustrated with a real data set.
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