Ro’ya Al Dibi’i, Rosmanjawati Abdul Rahman, Amjad Al-Nasser
{"title":"Fitting data to a multiple structural measurement errors model","authors":"Ro’ya Al Dibi’i, Rosmanjawati Abdul Rahman, Amjad Al-Nasser","doi":"10.1080/03610918.2024.2369802","DOIUrl":null,"url":null,"abstract":"This paper proposes two new estimation methods to fit a multiple structural measurement error model when all variables are subject to errors. The new estimation methods were extensions of the Wald ...","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":"32 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Statistics-Simulation and Computation","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/03610918.2024.2369802","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes two new estimation methods to fit a multiple structural measurement error model when all variables are subject to errors. The new estimation methods were extensions of the Wald ...
期刊介绍：
The Simulation and Computation series intends to publish papers that make theoretical and methodological advances relating to computational aspects of Probability and Statistics. Simulational assessment and comparison of the performance of statistical and probabilistic methods will also be considered for publication. Papers stressing graphical methods, resampling and other computationally intensive methods will be particularly relevant. In addition, special issues dedicated to a specific topic of current interest will also be published in this series periodically, providing an exhaustive and up-to-date review of that topic to the readership.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
