Arashi, MohammadNorouzirad, MinaRoozbeh, MahdiKhan, Naushad Mamode2022-09-152022-09-152021-11-28Arashi, M.; Norouzirad, M.; Roozbeh, M.; Khan, N.M. A High- Dimensional Counterpart for the Ridge Estimator in Multicollinear Situations. Mathematics 2021, 9, 3057. https://DOI.org/10.3390/math9233057.2227-739010.3390/math9233057https://repository.up.ac.za/handle/2263/87207The ridge regression estimator is a commonly used procedure to deal with multicollinear data. This paper proposes an estimation procedure for high-dimensional multicollinear data that can be alternatively used. This usage gives a continuous estimate, including the ridge estimator as a particular case. We study its asymptotic performance for the growing dimension, i.e., p→∞ when n is fixed. Under some mild regularity conditions, we prove the proposed estimator’s consistency and derive its asymptotic properties. Some Monte Carlo simulation experiments are executed in their performance, and the implementation is considered to analyze a high-dimensional genetic dataset.en© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.AsymptoticHigh–dimensionLiu estimatorMulticollinearRidge estimatorArticle