rvinecopulib: High Performance Algorithms for Vine Copula Modeling

In rvinecopulib: High Performance Algorithms for Vine Copula Modeling

High Performance Algorithms for Vine Copula Modeling

Description

Provides an interface to 'vinecopulib', a C++ library for vine copula modeling based on 'Boost' and 'Eigen'. The 'rvinecopulib' package implements the core features of the popular 'VineCopula' package, in particular inference algorithms for both vine copula and bivariate copula models. Advantages over 'VineCopula' are a sleeker and more modern API, improved performances, especially in high dimensions, nonparametric and multi-parameter families. The 'rvinecopulib' package includes 'vinecopulib' as header-only C++ library (currently version 0.6.2). Thus users do not need to install 'vinecopulib' itself in order to use 'rvinecopulib'. Since their initial releases, 'vinecopulib' is licensed under the MIT License, and 'rvinecopulib' is licensed under the GNU GPL version 3.

Author(s)

Thomas Nagler, Thibault Vatter

Examples

## bicop_dist objects
bicop_dist("gaussian", 0, 0.5)
str(bicop_dist("gauss", 0, 0.5))
bicop <- bicop_dist("clayton", 90, 3)

## bicop objects
u <- rbicop(500, "gauss", 0, 0.5)
fit1 <- bicop(u, family = "par")
fit1

## vinecop_dist objects
## specify pair-copulas
bicop <- bicop_dist("bb1", 90, c(3, 2))
pcs <- list(
  list(bicop, bicop), # pair-copulas in first tree
  list(bicop) # pair-copulas in second tree
)
## specify R-vine matrix
mat <- matrix(c(1, 2, 3, 1, 2, 0, 1, 0, 0), 3, 3)
## build the vinecop_dist object
vc <- vinecop_dist(pcs, mat)
summary(vc)

## vinecop objects
u <- sapply(1:3, function(i) runif(50))
vc <- vinecop(u, family = "par")
summary(vc)

## vine_dist objects
vc <- vine_dist(list(distr = "norm"), pcs, mat)
summary(vc)

## vine objects
x <- sapply(1:3, function(i) rnorm(50))
vc <- vine(x, copula_controls = list(family_set = "par"))
summary(vc)

rvinecopulib documentation built on March 7, 2023, 6:20 p.m.