Mahalanobis distance based on minimum regularized covariance determinant estimators for high dimensional data-Reference-Cited by-同舟云学术

Mahalanobis distance based on minimum regularized covariance determinant estimators for high dimensional data

Published:2020-01-29 Issue:24 Volume:49 Page:5897-5907
ISSN:0361-0926
Container-title:Communications in Statistics - Theory and Methods
language:en
Short-container-title:Communications in Statistics - Theory and Methods

Author:

Bulut Hasan¹

Affiliation:

1. Faculty of Science and Letters, Department of Statistics, Ondokuz Mayıs University, Samsun, Turkey

Publisher

Informa UK Limited

Subject

Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610926.2020.1719420

Reference16 articles.

1. The minimum regularized covariance determinant estimator

2. Influence Function and Efficiency of the Minimum Covariance Determinant Scatter Matrix Estimator

3. Guo, Y., T. Hastie, and R. Tibshirani. 2018. rda: Shrunken Centroids Regularized Discriminant Analysis. R package version 1.0.2-2.1. https://CRAN.R-project.org/package = rda

4. Three estimators of the Mahalanobis distance in high-dimensional data

5. ROBPCA: A New Approach to Robust Principal Component Analysis

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