120 citations · 545 across the 20 of their papers we have counts for
21 papers
Robust regularized covariance matrix estimation: well-posedness and convergent algorithm
Mengxi Yi, David Tyler
In this paper, we study properties of penalized and structured M-estimators of multivariate scatter, based on geodesically convex but not necessarily smooth penalty functions. Exis…
Robust and Resistant Regularized Covariance Matrices
David E. Tyler, Mengxi Yi, Klaus Nordhausen
We introduce a class of regularized M-estimators of multivariate scatter and show, analogous to the popular spatial sign covariance matrix (SSCM), that they possess high breakdown…
On the variability of the sample covariance matrix under complex elliptical distributions
Elias Raninen, Esa Ollila, David E. Tyler
We derive the form of the variance-covariance matrix for any affine equivariant matrix-valued statistics when sampling from complex elliptical distributions. We then use this resul…
Linear pooling of sample covariance matrices
Elias Raninen, David E. Tyler, Esa Ollila
We consider the problem of estimating high-dimensional covariance matrices of -populations or classes in the setting where the sample sizes are comparable to the data dimension.…
Breakdown points of penalized and hybrid M-estimators of covariance
David E. Tyler, Mengxi Yi
We introduce a class of hybrid M-estimators of multivariate scatter which, analogous to the popular spatial sign covariance matrix (SSCM), possess high breakdown points. We also sh…
Shrinking the Sample Covariance Matrix using Convex Penalties on the Matrix-Log Transformation
David E. Tyler, Mengxi Yi
For -dimensional data, penalized versions of the sample covariance matrix are important when the sample size is small or modest relative to . Since the negative log-likelihoo…