Modern science and industry rely on computational models for simulation,...
For a set of p-variate data points y_1,…,
y_n, there are several version...
We introduce a class of regularized M-estimators of multivariate scatter...
For high-dimensional data or data with noise variables, tandem clusterin...
Non-stationary source separation is a well-established branch of blind s...
We derive limiting distributions of symmetrized estimators of scatter, w...
Tensor-valued data benefits greatly from dimension reduction as the redu...
Invariant Coordinate Selection (ICS) is a multivariate data transformati...
Multivariate measurements at irregularly-spaced points and their analysi...
We develop projection pursuit for data that admit a natural representati...
Multivariate measurements taken at different spatial locations occur
fre...
Regional data analysis is concerned with the analysis and modeling of
me...
In stationary subspace analysis (SSA) one assumes that the observable
p-...
We study the estimation of the linear discriminant with projection pursu...
Temporal Blind Source Separation (TBSS) is used to obtain the true,
unde...
We assume a spatial blind source separation model in which the observed
...
Dimension reduction is a common strategy in multivariate data analysis w...
Sliced inverse regression is one of the most popular sufficient dimensio...
Compositional data represent a specific family of multivariate data, whe...
Partial orderings and measures of information for continuous univariate
...
Recently a blind source separation model was suggested for multivariate
...
In the independent component model, the multivariate data is assumed to ...
Supervised dimension reduction for time series is challenging as there m...
While an important topic in practice, the estimation of the number of
no...
In this work, we propose a novel method for tensorial independent compon...
We assume a second-order source separation model where the observed
mult...
We extend two methods of independent component analysis, fourth order bl...