Finite mixtures of regression models offer a flexible framework for investigating heterogeneity in data with functional dependencies. These models can be conveniently used for unsupervised learning on data with clear regression relationships. We extend such models by imposing an eigen-decomposition on the multivariate error covariance matrix. By constraining parts of this decomposition, we obta...

UNLABELLED We provide a new statistical algorithm and software package called 'eigen-R(2)' for dissecting the variation of a high-dimensional biological dataset with respect to other measured variables of interest. We apply eigen-R(2) to two real-life examples and compare it with simply averaging R(2) over many features. AVAILABILITY An R-package eigenR2 is available at http://www.genomine.or...

We prove polynomial and exponential decay at infinity of eigen-vectors of partial differential operators related to radiation problems for time-harmonic generalized Maxwell systems in an exterior domain Ω ⊂ RN , N ≥ 1, with non-smooth inhomogeneous, anisotropic coefficients converging near infinity with a rate r−τ , τ > 1, towards the identity. As a canonical application we show that the corres...

In this paper we critically analyze the so far performed and proposed tests for measuring the general relativistic Lense-Thirring effect in the gravitational field of the Earth with some of the existing accurately tracked artificial satellites. The impact of the 2nd generation GRACE-only EIGEN-GRACE02S Earth gravity model and of the 1st CHAMP+GRACE+terrestrial gravity combined EIGEN-CG01C Earth...

The convergence of iterative methods used to solve the linear equations arising from radiosity systems depends on the distribution of the eigenvalues of the radiosity coefficient matrix. In this paper we prove that all eigenvalues of the radiosity coefficient matrix are real and positive. This fact may allow us to obtain fast radiosity solutions using the knowledge about the spectrum of the mat...