The regressions of least absolute shrinkage and selection operator with applications

Saleh, Aseel Noori

doi:10.22075/ijnaa.2022.6553

The regressions of least absolute shrinkage and selection operator with applications

Document Type : Research Paper

Author

Aseel Noori Saleh

Department of Studies, Planning and Follow-up, Ministry of Higher Education and Scientific Research, Iraq

10.22075/ijnaa.2022.6553

Abstract

Lasso regression model is a causal model based on providing a more accurate estimator through the model's dependence on shrinkage, in which the data values were reduced towards the data center. This model solves the problems of multicollinearity presence of high relationships between the explanatory variables of the model. In this research, a number of factors (sample size, number of explanatory variables and pollution rate) were adopted in order to observe the ability of these factors to effect Lasso regression.

Keywords

LASSO regressions

Mean Square Error

multicollinearity

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