Alfira Mulya Astuti, Setiawan, I. Zain, J. Purnomo
{"title":"The extended algorithm for quasi maximum likelihood parameter estimation","authors":"Alfira Mulya Astuti, Setiawan, I. Zain, J. Purnomo","doi":"10.1063/5.0059509","DOIUrl":null,"url":null,"abstract":"This research aims to develop an algorithm of the quasi maximum likelihood estimation method. The model used is the spatial Durbin panel model with dynamic effects for the single equation. The weighted matrix used in this study is equal for each variable This study proposes the generalized estimation equation approach and the Gauss-Newton iteration method for parameter estimation. Modeling of Foreign Direct Investment (FDI) in ASEAN countries from 2010 - 2017 is used for illustration. The best model selection is based on the smallest correlation information criterion (CIC) value.","PeriodicalId":13712,"journal":{"name":"INTERNATIONAL CONFERENCE ON ENERGY AND ENVIRONMENT (ICEE 2021)","volume":"44 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"INTERNATIONAL CONFERENCE ON ENERGY AND ENVIRONMENT (ICEE 2021)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1063/5.0059509","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This research aims to develop an algorithm of the quasi maximum likelihood estimation method. The model used is the spatial Durbin panel model with dynamic effects for the single equation. The weighted matrix used in this study is equal for each variable This study proposes the generalized estimation equation approach and the Gauss-Newton iteration method for parameter estimation. Modeling of Foreign Direct Investment (FDI) in ASEAN countries from 2010 - 2017 is used for illustration. The best model selection is based on the smallest correlation information criterion (CIC) value.
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