International Journal of Nonlinear Analysis and Applications
The regressions of least absolute shrinkage and selection operator with applications
Document Type : Research Paper
Author
Department of Studies, Planning and Follow-up, Ministry of Higher Education and Scientific Research, Iraq
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
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Volume 13, Issue 2
July 2022Pages 1735-1746
- Receive Date: 05 January 2022
- Revise Date: 02 March 2022
- Accept Date: 18 March 2022