[BOOK][B] Robust statistics: theory and methods (with R)
A new edition of this popular text on robust statistics, thoroughly updated to include new and
improved methods and focus on implementation of methodology using the increasingly …
improved methods and focus on implementation of methodology using the increasingly …
Minimum volume ellipsoid
The minimum volume ellipsoid (MVE) estimator is based on the smallest volume ellipsoid
that covers h of the n observations. It is an affine equivariant, high‐breakdown robust …
that covers h of the n observations. It is an affine equivariant, high‐breakdown robust …
Agnostic estimation of mean and covariance
We consider the problem of estimating the mean and covariance of a distribution from iid
samples in the presence of a fraction of malicious noise. This is in contrast to much recent …
samples in the presence of a fraction of malicious noise. This is in contrast to much recent …
Robust estimates of location and dispersion for high-dimensional datasets
The computing times of high-breakdown point estimates of multivariate location and scatter
increase rapidly with the number of variables, which makes them impractical for high …
increase rapidly with the number of variables, which makes them impractical for high …
High-breakdown robust multivariate methods
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 …
from the usual assumptions. However, many classical methods are sensitive to outliers. The …
The behavior of the Stahel-Donoho robust multivariate estimator
Abstract The Stahel-Donoho estimators (t, V) of multivariate location and scatter are defined
as a weighted mean and a weighted covariance matrix with weights of the form w (r), where …
as a weighted mean and a weighted covariance matrix with weights of the form w (r), where …
[BOOK][B] Robust statistical methods with R
J Jureckova, J Picek - 2005 - taylorfrancis.com
Robust statistical methods were developed to supplement the classical procedures when
the data violate classical assumptions. They are ideally suited to applied research across a …
the data violate classical assumptions. They are ideally suited to applied research across a …
Invariant co-ordinate selection
DE Tyler, F Critchley, L Dümbgen… - Journal of the Royal …, 2009 - academic.oup.com
A general method for exploring multivariate data by comparing different estimates of
multivariate scatter is presented. The method is based on the eigenvalue–eigenvector …
multivariate scatter is presented. The method is based on the eigenvalue–eigenvector …
A practical affine equivariant multivariate median
TP Hettmansperger, RH Randles - Biometrika, 2002 - academic.oup.com
A robust affine equivariant estimator of location for multivariate data is proposed which
becomes the univariate median for data of dimension one. The estimator is robust in the …
becomes the univariate median for data of dimension one. The estimator is robust in the …
On Tyler's M-functional of scatter in high dimension
L Dümbgen - Annals of the Institute of Statistical Mathematics, 1998 - Springer
Abstract Let y 1, y 2,..., yn∈ R q be independent, identically distributed random vectors with
nonsingular covariance matrix Σ, and let S= S (y 1,..., yn) be an estimator for Σ. A quantity of …
nonsingular covariance matrix Σ, and let S= S (y 1,..., yn) be an estimator for Σ. A quantity of …