We study multivariate Gaussian statistical models whose maximum likeliho...
The recently introduced graphical continuous Lyapunov models provide a n...
In this paper we study linear non-Gaussian graphical models from the
per...
The method of moments is a statistical technique for density estimation ...
Max-linear Bayesian networks have emerged as highly applicable models fo...
We introduce the package GraphicalModelsMLE for computing the maximum
li...
We establish connections between invariant theory and maximum likelihood...
Correlation matrices are standardized covariance matrices. They form an
...
We study multivariate Gaussian models that are described by linear condi...
We consider the problem of structure learning for linear causal models b...
We show that maximum likelihood estimation in statistics is equivalent t...
Motivated by extreme value theory, max-linear Bayesian networks have bee...
We study the maximum likelihood estimation problem for several classes o...
We consider the problem of identifying a mixture of Gaussian distributio...
We study the autocovariance functions of moving average random fields ov...
We introduce a discrete analogue of the classical multivariate Gaussian
...