JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2026, Vol. 61 ›› Issue (9): 49-55.doi: 10.6040/j.issn.1671-9352.0.2024.120

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Robustness comparison of ROBPCA methods

FANG Hongyan, ZHANG Qiaoqiao, YANG Xinyu   

  1. School of Big Data and Statistics, Anhui University, Hefei 230601, Anhui, China
  • Published:2026-09-30

Abstract: An adaptive robust PCA method is developed by employing the CUSUM chart method in change point detection. The outlier detection performances of robust PCA methods are compared through numerous simulation studies. The robust PCA based on the CUSUM chart method obtains the closest sample size to the true value, has the highest screening accuracy, and has a superior performance even when the variable dimension becomes larger. The analysis and application of the actual data of national economic indicators in counties and cities in Zhejiang province also verifies the accuracy and reliability of this method.

Key words: ROBPCA, outliers, PCA method, MCD method, FAST-MCD method, ROBPCA method, change point detection, CUSUM method

CLC Number: 

  • O212
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