Ridge and Lasso Regression for Undergraduate Research with Simulation in R

Di Gao, Xiyuan Liu, Stephen Scariano

Abstract: A key part of the undergraduate statistics curriculum is modeling and prediction. Indeed, regression analysis is one of the most frequently used statistical methods in the sciences. Most introductory statistics textbooks contain one or more chapters discussing regression methodology. However, with the advent of big data problems, the classical discussion of introductory regression analysis may not fully capture the current state of the art. This article presents an undergraduate perspective for regression analysis with regulation. Our discussion concentrates on the methodology which is then followed by an informative simulation study.

Keywords: Ridge, Lasso, Simulation, R

How to Cite?: Di Gao, Xiyuan Liu, Stephen Scariano, "Ridge and Lasso Regression for Undergraduate Research with Simulation in R", Volume 9 Issue 1, January 2020, International Journal of Science and Research (IJSR), Pages: 968-970, https://www.ijsr.net/getabstract.php?paperid=ART20203892, DOI: https://dx.doi.org/10.21275/ART20203892

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