Robust multiple-set linear canonical analysis based on minimum covariance determinant estimator

Abstract

In this paper, we introduce a robust version of multiple-set linear canonical analysis (MSLCA) by using the MCD estimator of the covariance operator of the involved random vector. The related influence functions are derived and are shown to be bounded. Asymptotic properties of the introduced robust MSLCA are obtained and allow us to propose a robust test for mutual non correlation. A simulation study, which shows that this test outperforms classical ones in the presence of disturbed data, is presented.