{"title":"广义拟林德利分布:理论性质、估计方法及应用","authors":"A. Al-Omari, SidAhmed Benchiha","doi":"10.1285/I20705948V14N1P167","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a new continuous distribution of two parameterscalled as a generalized Quasi Lindley distribution (GQLD). The GQLD is asum of two independent Quasi Lindley distributed random variables. Compre-hensive statistical properties of the GQLD are provided in closed forms includesmoments, reliability analysis, stochastic ordering, stress-strength reliability, andthe distribution of order statistics. The parameters of the new distribution areestimated by the maximum likelihood, maximum product of spacings, ordinaryleast squares, weighted least squares, Cramer-von-Mises, and Anderson-Darlingmethods are considered. A simulation study is conducted to investigate theeciency of the proposed estimators and applications to real data sets are pro-vided.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"14 1","pages":"167-196"},"PeriodicalIF":0.6000,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Generalized Quasi Lindley Distribution: Theoretical Properties, Estimation Methods, and Applications\",\"authors\":\"A. Al-Omari, SidAhmed Benchiha\",\"doi\":\"10.1285/I20705948V14N1P167\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce a new continuous distribution of two parameterscalled as a generalized Quasi Lindley distribution (GQLD). The GQLD is asum of two independent Quasi Lindley distributed random variables. Compre-hensive statistical properties of the GQLD are provided in closed forms includesmoments, reliability analysis, stochastic ordering, stress-strength reliability, andthe distribution of order statistics. The parameters of the new distribution areestimated by the maximum likelihood, maximum product of spacings, ordinaryleast squares, weighted least squares, Cramer-von-Mises, and Anderson-Darlingmethods are considered. A simulation study is conducted to investigate theeciency of the proposed estimators and applications to real data sets are pro-vided.\",\"PeriodicalId\":44770,\"journal\":{\"name\":\"Electronic Journal of Applied Statistical Analysis\",\"volume\":\"14 1\",\"pages\":\"167-196\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2021-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronic Journal of Applied Statistical Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1285/I20705948V14N1P167\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Journal of Applied Statistical Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1285/I20705948V14N1P167","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Generalized Quasi Lindley Distribution: Theoretical Properties, Estimation Methods, and Applications
In this paper, we introduce a new continuous distribution of two parameterscalled as a generalized Quasi Lindley distribution (GQLD). The GQLD is asum of two independent Quasi Lindley distributed random variables. Compre-hensive statistical properties of the GQLD are provided in closed forms includesmoments, reliability analysis, stochastic ordering, stress-strength reliability, andthe distribution of order statistics. The parameters of the new distribution areestimated by the maximum likelihood, maximum product of spacings, ordinaryleast squares, weighted least squares, Cramer-von-Mises, and Anderson-Darlingmethods are considered. A simulation study is conducted to investigate theeciency of the proposed estimators and applications to real data sets are pro-vided.