{"title":"弗雷谢特分布的对数矩估计法","authors":"Victor Nawa , Saralees Nadarajah","doi":"10.1016/j.cam.2024.116293","DOIUrl":null,"url":null,"abstract":"<div><div>New estimators for the Fréchet distribution based on the method of logarithmic moments are proposed. These are the first estimators for the Fréchet distribution taking closed forms and applicable for all parameter values. Large sample properties of the proposed estimators are derived. The proposed estimators are compared to the maximum likelihood estimators by simulation.</div></div>","PeriodicalId":50226,"journal":{"name":"Journal of Computational and Applied Mathematics","volume":"457 ","pages":"Article 116293"},"PeriodicalIF":2.1000,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Logarithmic method of moments estimators for the Fréchet distribution\",\"authors\":\"Victor Nawa , Saralees Nadarajah\",\"doi\":\"10.1016/j.cam.2024.116293\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>New estimators for the Fréchet distribution based on the method of logarithmic moments are proposed. These are the first estimators for the Fréchet distribution taking closed forms and applicable for all parameter values. Large sample properties of the proposed estimators are derived. The proposed estimators are compared to the maximum likelihood estimators by simulation.</div></div>\",\"PeriodicalId\":50226,\"journal\":{\"name\":\"Journal of Computational and Applied Mathematics\",\"volume\":\"457 \",\"pages\":\"Article 116293\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational and Applied Mathematics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0377042724005417\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational and Applied Mathematics","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0377042724005417","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Logarithmic method of moments estimators for the Fréchet distribution
New estimators for the Fréchet distribution based on the method of logarithmic moments are proposed. These are the first estimators for the Fréchet distribution taking closed forms and applicable for all parameter values. Large sample properties of the proposed estimators are derived. The proposed estimators are compared to the maximum likelihood estimators by simulation.
期刊介绍:
The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest.
The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.