{"title":"Closed-form estimators for the inverse Nakagami distribution.","authors":"Victor Nawa, Saralees Nadarajah","doi":"10.1590/0001-3765202520240838","DOIUrl":null,"url":null,"abstract":"<p><p>The inverse Nakagami distribution due to Louzada et al. (2018) does not have closed-form maximum likelihood estimators. Closed-form estimators by adapting the method of moments are proposed in this note. Also proposed is a bias corrected version of the estimators. Large sample properties including asymptotic variances of the proposed estimators are derived. A simulation study and data applications are provided to compare the performances of the maximum likelihood estimators, the proposed estimators and their bias corrected versions.</p>","PeriodicalId":7776,"journal":{"name":"Anais da Academia Brasileira de Ciencias","volume":"97 1","pages":"e20240838"},"PeriodicalIF":1.1000,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anais da Academia Brasileira de Ciencias","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1590/0001-3765202520240838","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The inverse Nakagami distribution due to Louzada et al. (2018) does not have closed-form maximum likelihood estimators. Closed-form estimators by adapting the method of moments are proposed in this note. Also proposed is a bias corrected version of the estimators. Large sample properties including asymptotic variances of the proposed estimators are derived. A simulation study and data applications are provided to compare the performances of the maximum likelihood estimators, the proposed estimators and their bias corrected versions.
期刊介绍:
The Brazilian Academy of Sciences (BAS) publishes its journal, Annals of the Brazilian Academy of Sciences (AABC, in its Brazilianportuguese acronym ), every 3 months, being the oldest journal in Brazil with conkinuous distribukion, daking back to 1929. This scienkihic journal aims to publish the advances in scienkihic research from both Brazilian and foreigner scienkists, who work in the main research centers in the whole world, always looking for excellence.
Essenkially a mulkidisciplinary journal, the AABC cover, with both reviews and original researches, the diverse areas represented in the Academy, such as Biology, Physics, Biomedical Sciences, Chemistry, Agrarian Sciences, Engineering, Mathemakics, Social, Health and Earth Sciences.