تقدير انموذج انحدار لاسو الضبابي

Rawya Emad Kareem; Mohammed Jasim Mohammed

doi:10.51173/jt.v5i4.1329

Authors

Rawya Emad Kareem College of Administration & Economics, University of Baghdad, Baghdad, Iraq
Mohammed Jasim Mohammed College of Administration & Economics, University of Baghdad, Baghdad, Iraq

DOI:

https://doi.org/10.51173/jt.v5i4.1329

Keywords:

Fuzzy Least Squares, Fuzzy Regression, Fuzzy Lasso Regression, Fuzzy Numbers, Triangular Function

Abstract

Estimating the fuzzy lasso regression model when the data suffers from the problem of multicollinearity because of the failure of using the fuzzy least squares method in estimating the model by using the fuzzy theory using a triangular function, as the fuzzy lasso regression gives better results by comparing the results with the squares method fuzzy minimum using the mean square error (MSE) criterion The simulation results showed that the fuzzy lasso regression method gave less MSE than the fuzzy least squares method in the presence of the problem of multicollinearity in the data.

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Author Biographies

Rawya Emad Kareem, College of Administration & Economics, University of Baghdad, Baghdad, Iraq

Department of Statistics

Mohammed Jasim Mohammed, College of Administration & Economics, University of Baghdad, Baghdad, Iraq

Department of Statistics

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