The minimum covariance determinant (MCD) method is a highly robust estimator of
multivariate location and scatter, for which a fast algorithm is available. Since estimating the …

The minimum covariance determinant (MCD) estimator is a highly robust estimator of
multivariate location and scatter. It can be computed efficiently with the FAST‐MCD …

Cronbach's alpha is a popular method to measure reliability, eg in quantifying the reliability
of a score to summarize the information of several items in questionnaires. The alpha …

When applying a statistical method in practice it often occurs that some observations deviate
from the usual assumptions. However, many classical methods are sensitive to outliers. The …

Our aim is to construct a factor analysis method that can resist the effect of outliers. For this
we start with a highly robust initial covariance estimator, after which the factors can be …

Most algorithms for highly robust estimators of multivariate location and scatter start by
drawing a large number of random subsets. For instance, the FASTMCD algorithm of …

Before implementing any multivariate statistical analysis based on empirical covariance
matrices, it is important to check whether outliers are present because their existence could …

Background Canonical correlation analysis (CCA) is a multivariate statistical method which
describes the associations between two sets of variables. The objective is to find linear …

In this paper, the influence functions and limiting distributions of the canonical correlations
and coefficients based on affine equivariant scatter matrices are developed for elliptically …

Several approaches for robust canonical correlation analysis will be presented and
discussed. A first method is based on the definition of canonical correlation analysis as …