This paper proposes a nonparametric multivariate density forecast model based on deep learning. It not only offers the whole marginal distribution of each random variable in forecasting targets, but ...

The copula function’s fundamental concept is to link the marginal distribution to the joint distribution (Sklar, 1959), avoiding direct estimation of the multivariate distribution function and fitting ...

In recent years, the non-stationarity in multivariate hydrological series has just begun to attract some attention only recently (Xiong et al., 2015). Some studies have introduced the non-stationarity ...

We develop a family of copula-based multivariate distributions with g-and-h marginal distributions.; A distribution based on a single copula is not flexible enough, and thus we model the dependence ...

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 ...

Implements a truncated multivariate normal distribution - gzheng92/TMvNormals.jl. Skip to content. Navigation Menu Toggle navigation. Sign in ... (d, zeros(3)) # evaluates the joint density let d = 1 ...