Online Program Home
  My Program

All Times EDT

Abstract Details

Activity Number: 245 - SLDS CSpeed 4
Type: Contributed
Date/Time: Wednesday, August 11, 2021 : 10:00 AM to 11:50 AM
Sponsor: Section on Statistical Learning and Data Science
Abstract #318263
Title: Robust Criterion for Multicollinear Factor Selection
Author(s): Kimon Ntotsis* and Alex Karagrigoriou and Andreas Artemiou
Companies: University of the Aegean and University of the Aegean and Cardiff University
Keywords: Multicollinearity Detection; Elastic Net Regularization; Model Selection Criteria; Coefficient Penalization; Factor Over-elimination

When it comes to factor interpretation, multicollinearity is among the biggest issues that must be surmounted especially in this new era, of Big Data Analytics. Since even moderate size multicollinearity can prevent a proper interpretation, special diagnostics must be recommended and implemented for identification purposes. In this work, we propose the Elastic Information Criterion which is capable of capturing multicollinearity accurately and effectively without factor over-elimination. The performance in simulated and real numerical studies is demonstrated.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2021 program