In this talk, the R-package VineCopula will be presented and illustrated by means of an example data set. The package contains functions for statistical inference of vine copulas and tools for exploratory data analysis and selection of bivariate copulas as building blocks of vine copulas. Vine trees can be selected using a tree-by-tree approach. Models can be estimated by joint maximum likelihood estimation and standard errors of model parameters are provided. Algorithms for sampling and illustrating vine copulas are also included.Non UBCUnreviewedAuthor affiliation: Technische Universitaet MuenchenGraduat
In this paper, we present a new methodology based on vine copulas to estimate multivariate distribut...
In this paper, we present a new methodology based on vine copulas to estimate multivariate distribut...
vinecopulib is a header-only C++ library for vine copula models based on Eigen. It provides high-per...
Imports MASS, mvtnorm, graphics, igraph, stats Description Functions for statistical inference of ca...
This textbook provides a step-by-step introduction to the class of vine copulas, their statistical i...
Depends R (> = 2.11.0), MASS, mvtnorm, igraph Description This package provides functions for sta...
We present a new recursive algorithm to construct vine copulas based on an underlying tree structure...
Flexible multivariate distributions are needed in many areas. The popular multivariate Gaussian dist...
We present a new recursive algorithm to construct vine copulas based on an underlying tree structure...
This thesis contributes to research in multivariate statistics by developing regular vine copula-bas...
International audienceWe present a new recursive algorithm to construct vine copulas based on an und...
We present a new recursive algorithm to construct vine copulas based on an underlying tree structure...
Copulas are important models that allow to capture the dependence among variables. There are many ty...
To uncover complex hidden dependency structures among variables, researchers have used a mixture of ...
Copulas are widely used in high-dimensional multivariate applications where the assumption of Gaussi...
In this paper, we present a new methodology based on vine copulas to estimate multivariate distribut...
In this paper, we present a new methodology based on vine copulas to estimate multivariate distribut...
vinecopulib is a header-only C++ library for vine copula models based on Eigen. It provides high-per...
Imports MASS, mvtnorm, graphics, igraph, stats Description Functions for statistical inference of ca...
This textbook provides a step-by-step introduction to the class of vine copulas, their statistical i...
Depends R (> = 2.11.0), MASS, mvtnorm, igraph Description This package provides functions for sta...
We present a new recursive algorithm to construct vine copulas based on an underlying tree structure...
Flexible multivariate distributions are needed in many areas. The popular multivariate Gaussian dist...
We present a new recursive algorithm to construct vine copulas based on an underlying tree structure...
This thesis contributes to research in multivariate statistics by developing regular vine copula-bas...
International audienceWe present a new recursive algorithm to construct vine copulas based on an und...
We present a new recursive algorithm to construct vine copulas based on an underlying tree structure...
Copulas are important models that allow to capture the dependence among variables. There are many ty...
To uncover complex hidden dependency structures among variables, researchers have used a mixture of ...
Copulas are widely used in high-dimensional multivariate applications where the assumption of Gaussi...
In this paper, we present a new methodology based on vine copulas to estimate multivariate distribut...
In this paper, we present a new methodology based on vine copulas to estimate multivariate distribut...
vinecopulib is a header-only C++ library for vine copula models based on Eigen. It provides high-per...