We start with analyzing stochastic dependence in a classic bivariate normal density framework. We focus on the way the conditional density of one of the random variables depends on realizations of the ...

The Poisson distribution has been widely studied and used for modeling univariate count-valued data. Multivariate generalizations of the Poisson distribution that permit dependencies, however, have ...

We propose a family of copula-based multivariate distributions with g-and-h marginals. After studying the properties of the distribution, we develop a two-step estimation strategy and analyze via ...

Abstract: Univariate Mixed Poisson distributions (MPDs) are commonly used to model data recorded from low flux objects or with short exposure times. They assume that the number of recorded events, ...

Abstract: In this article, the tail dependence coefficient of the multivariate elliptical distribution and its properties are obtained. Furthermore, some specific tail dependence coefficients (TDC) ...

The multivariate t distribution implementation is based on the code of Gregory Gunderson: https://github.com/gwgundersen/multivariate-t-distribution. While the code ...

This repository contains parts of the implementation code for the projects 'Structured Uncertainty Prediction Networks' (CVPR 2018) and 'Training VAEs Under Structured Residuals' (arxiv 2018). This ...