COMPARE BETWEEN ORDINARY LEAST SQUARE AND MAXIMUM LIKELIHOOD METHODS FOR ESTIMATE PARAMETER OF FUZZY SPATIAL LAG MODEL

dc.contributor.authorJaufar Mousa Mohammed
dc.contributor.authorMaySoon M. Aziz
dc.contributor.authorAmmer Fadel Tawfeeq
dc.date.accessioned2025-12-31T13:01:56Z
dc.date.issued2021-01-31
dc.description.abstractThis paper deals with the study about the formulation of Spatial Lag model for independent and dependent fuzzy variables. while the parameters crisp values, with compare between ordinary least square (OLS) and maximum likelihood (MLE) methods to Estimate Parameters by Criteria Root Mean Squares Error ( RMSE) and Mean Absolute Percentage Error (MAPE) ,we get results that (OLS) the best from (MLS) for Trapezoidal fuzzy number in the domain traffic accidents for a number of cities in Iraq for the year 2018.and that after converting the Trapezoidal fuzzy number into crisp values by centriod method , calculations the results by Matlab language.
dc.formatapplication/pdf
dc.identifier.urihttps://scholarexpress.net/index.php/wbml/article/view/504
dc.identifier.urihttps://asianeducationindex.com/handle/123456789/45561
dc.language.isoeng
dc.publisherScholar Express Journals
dc.relationhttps://scholarexpress.net/index.php/wbml/article/view/504/470
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0
dc.sourceWorld Bulletin of Management and Law; Vol. 6 (2022): WBML; 79-86
dc.source2749-3601
dc.subjectFuzz spatial regression models
dc.subjectFuzzy Spatial Lag
dc.subjectcentriod method
dc.titleCOMPARE BETWEEN ORDINARY LEAST SQUARE AND MAXIMUM LIKELIHOOD METHODS FOR ESTIMATE PARAMETER OF FUZZY SPATIAL LAG MODEL
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Article

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