Performances of some high dimensional regression methods. Issue 6 (5th July 2021)

• Record Type: Journal Article
• Authors: Kurnaz, Fatma Sevinç
• Is Part Of: Communications in statistics. Volume 50:Issue 6(2021)
• Page Start: 1820
• Page End: 1836
• Publication Date: 2021-07-05
• Subjects: lasso -- L1 penalty -- Robustness -- Variable selection; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2021.1881115
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract: Variable selection is one of the important practical issues for many scientific areas, particularly in chemometrics, where data sets include several hundreds of variables and low number of observations. The aim of this paper is to compare some newly proposed variable selection methods by means of extensive simulation studies and to give some practical hints for use of the compared methods. Furthermore, we underpin the performances of compared methods based on real data examples.