5 papers
Robust PCA with FastHCS
E. Schmitt, K. Vakili
Principal component analysis (PCA) is widely used to analyze high-dimensional data, but it is very sensitive to outliers. Robust PCA methods seek fits that are unaffected by the ou…
Finite Sample Breakdown of PCS
Eric Schmitt, Viktoria Oellerer, Kaveh Vakili
The Projection Congruent Subset (PCS) is new method for finding multivariate outliers. PCS returns an outlyingness index which can be used to construct affine equivariant estimates…
Finding Regression Outliers With FastRCS
Kaveh Vakili, Eric Schmitt
The Residual Congruent Subset (RCS) is a new method for finding outliers in the linear regression setting. Like many other outlier detection procedures, RCS searches for a subset w…
Finding Multivariate Outliers With FastPCS
Kaveh Vakili, Eric Schmitt
The Projection Congruent Subset (PCS) Outlyingness is a new index of multivariate outlyingness obtained by considering univariate projections of the data. Like many other outlier d…
The Multivariate Estimator
Kaveh Vakili
In this note we introduce the M estimator (for Multivariate ) a new robust estimator of multivariate ranking. Like MVE and MCD it searches for an -subset which minimiz…