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The regressions of least absolute shrinkage and selection operator with applications | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 139، دوره 13، شماره 2، مهر 2022، صفحه 1735-1746 اصل مقاله (923.33 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.6553 | ||
| نویسنده | ||
| Aseel Noori Saleh* | ||
| Department of Studies, Planning and Follow-up, Ministry of Higher Education and Scientific Research, Iraq | ||
| تاریخ دریافت: 15 دی 1400، تاریخ بازنگری: 11 اسفند 1400، تاریخ پذیرش: 27 اسفند 1400 | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| LASSO regressions؛ Mean Square Error؛ multicollinearity | ||
| مراجع | ||
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[1] R. Alhamzawi, K. Yu and D.F. Benoit, Bayesian adaptive LASSO quantile regression, Statist. Model. 12 (2012), no. 3, 279–297. [2] N. Gauraha, Introduction to the LASSO, Resonance 23 (2018), no. 4, 439–464. [3] C. Hans, Bayesian LASSO regression, Biometrika 96 (2009), no. 4, 835–845. [4] L. Meier, De. Van, S. Geer and P. B¨uhlmann, The group LASSO for logistic regression, J. Royal Statist. Soc.: Ser. B 70 (2008), no. 1, 53–71. [5] J. Ranstam and J. Cook, LASSO regression, J. Br. Surgery 105 (2018), no. 10, 1348–1348. [6] V. Roth. The generalized LASSO, IEEE Trans. Neural Networks 15 (2004), no. 1, 16–28. [7] S.S. Roy, D. Mittal, A. Basu and A. Abraham, Stock market forecasting using LASSO linear regression model, Afro-Eur. Conf. Ind. Adv. Springer, 2015, pp. 371–381. [8] C. Sun, B. Zhu, S. Zhu, L. Zhang, X. Du and X. Tan. Risk factors analysis of bone mineral density based on LASSO and Quantile regression in America during 2015–2018, Int. J. Envir. Res. Public Health 19 (2022), no. 1, 355. [9] R. Tibshirani, Regression shrinkage and selection via the LASSO, J. Royal Statist. Soc. Ser. B 58 (1996), no. 1, 267–288. | ||
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