RVineCDF {VineCopula} | R Documentation |
CDF of an R-Vine Copula Model
Description
This function calculates the cumulative distribution function of a d-dimensional R-vine copula.
Usage
RVineCDF(data, RVM, N = 1000)
Arguments
data |
An N x d data matrix that specifies where the CDF shall be evaluated. |
RVM |
An |
N |
Number of points to simulate for the Monte
Carlo integration (default: |
Details
The cumulative distribution function of a d
-dimensional R-vine copula
cannot be expressed in closed form.
However, it can be calculated by numerical integration. The function uses
the RVineSim()
function to
simulate a grid of points and then computes the CDF via Monte Carlo.
Value
A vector of length N with the CDF values.
Author(s)
Thibault Vatter
See Also
RVineSim()
, RVineMatrix()
, RVineLogLik()
, RVinePDF()
Examples
# define 5-dimensional R-vine tree structure matrix
Matrix <- c(
5, 2, 3, 1, 4,
0, 2, 3, 4, 1,
0, 0, 3, 4, 1,
0, 0, 0, 4, 1,
0, 0, 0, 0, 1
)
Matrix <- matrix(Matrix, 5, 5)
# define R-vine pair-copula family matrix
family <- c(
0, 1, 3, 4, 4,
0, 0, 3, 4, 1,
0, 0, 0, 4, 1,
0, 0, 0, 0, 3,
0, 0, 0, 0, 0
)
family <- matrix(family, 5, 5)
# define R-vine pair-copula parameter matrix
par <- c(
0, 0.2, 0.9, 1.5, 3.9,
0, 0, 1.1, 1.6, 0.9,
0, 0, 0, 1.9, 0.5,
0, 0, 0, 0, 4.8,
0, 0, 0, 0, 0
)
par <- matrix(par, 5, 5)
# define second R-vine pair-copula parameter matrix
par2 <- matrix(0, 5, 5)
# define RVineMatrix object
RVM <- RVineMatrix(
Matrix = Matrix, family = family,
par = par, par2 = par2,
names = c("V1", "V2", "V3", "V4", "V5")
)
# compute the CDF at (0.1, 0.2, 0.3, 0.4, 0.5)
RVineCDF(c(0.1, 0.2, 0.3, 0.4, 0.5), RVM)
[Package VineCopula version 2.6.0 Index]