RVineMatrixSample: Random sampling of R-Vine matrices

In tnagler/VineCopula: Statistical Inference of Vine Copulas

Random sampling of R-Vine matrices

Description

Sample R-Vine matrices based on the algorithm of Joe et al. (2011).

Usage

RVineMatrixSample(d, size = 1, naturalOrder = FALSE)

Arguments

d	Dimension of the R-Vine matrices.
size	Number of matrices to sample.
naturalOrder	Should the matrices be in the natural order (default: naturalOrder = FALSE).

Value

A list of length size with each element containing one R-Vine matrix.

Note

For some reason, our implementation of Joe et al.'s algorithm always returns a star in the first tree. To fix this, we sample a vine matrix of dimension d + 1 and remove the first tree afterwards

Author(s)

Thibault Vatter

References

Joe H, Cooke RM and Kurowicka D (2011). Regular vines: generation algorithm and number of equivalence classes. In Dependence Modeling: Vine Copula Handbook, pp 219–231. World Scientific, Singapore.

See Also

RVineMatrix(), RVineMatrixCheck()

Examples

# Matrix and sample sizes
d <- 10
size <- 5

# Sample R-vine matrices
RVM <- RVineMatrixSample(d, size)
sapply(RVM, RVineMatrixCheck)

# Sample R-vine matrices in the natural order
RVM <- RVineMatrixSample(d, size, naturalOrder = TRUE)
sapply(RVM, RVineMatrixCheck)

tnagler/VineCopula documentation built on March 6, 2024, 5 a.m.