Minimum regularized covariance determinant and principal component analysis-based method for the identification of high leverage points in high dimensional sparse data

• Main Authors: Siti Zahariah, Midi, Habshah
• Format: Article
• Published: Taylor and Francis 2022
• Online Access: http://psasir.upm.edu.my/id/eprint/102186/; https://www.tandfonline.com/doi/abs/10.1080/02664763.2022.2093842?journalCode=cjas20

The main aim of this paper is to propose a novel method (RMD-MRCD-PCA) of identification of High Leverage Points (HLPs) in high-dimensional sparse data. It is to address the weakness of the Robust Mahalanobis Distance (RMD) method which is based on the Minimum Regularized Covariance Determinant (RMD...