{"title":"ASYMPTOTIC NORMALITY OF TRIMMED L-MOMENTS ESTIMATOR FOR ARCHIMEDEAN COPULAS","authors":"Idiou Nesrine, Benatia Fatah","doi":"10.46939/j.sci.arts-23.1-a12","DOIUrl":null,"url":null,"abstract":"In order to present a new estimation approach for multi-parameter distributions without a mean or for heavy tailed distributions, in which the L-moments method proposed by Gumbel, (1960), is invalid due to the absence of theoretical L-moments, Trimmed L-moments were first introduced by Elamir and Seheult (2003). In this paper, a new estimation method based on multi-parameter copulas' Trimmed L-moments is proposed with a simulation study. The consistency and the asymptotic normality of the new estimator also established.","PeriodicalId":54169,"journal":{"name":"Journal of Science and Arts","volume":" ","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Science and Arts","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46939/j.sci.arts-23.1-a12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
In order to present a new estimation approach for multi-parameter distributions without a mean or for heavy tailed distributions, in which the L-moments method proposed by Gumbel, (1960), is invalid due to the absence of theoretical L-moments, Trimmed L-moments were first introduced by Elamir and Seheult (2003). In this paper, a new estimation method based on multi-parameter copulas' Trimmed L-moments is proposed with a simulation study. The consistency and the asymptotic normality of the new estimator also established.
针对Gumbel(1960)提出的l -矩方法由于缺乏理论l -矩而失效的无均值多参数分布或重尾分布,为了提出一种新的估计方法,Elamir和Seheult(2003)首先引入了trim l -矩。本文通过仿真研究,提出了一种基于多参数copula裁剪l矩的估计方法。并证明了新估计量的相合性和渐近正态性。