varray2M: Vine array to maximum matrix

In YafeiXu/CopulaModel: CopulaModel: Dependence Modeling with Copulas

Description

Vine array to maximum matrix

Usage

varray2M(A,iprint=F,str="")

Arguments

A	dxd vine array with 1:d on diagonal; only upper triangle is used
iprint	print flag for some intermediate steps
str	string to describe the vine if iprint=T

Details

In the VineCopula R package and in "Dissmann J, Brechmann EC, Czado C and Kurowicka D (2013). Computational Statistics and Data Analysis, 59, 52-69", the vine array is abbreviation as RVM and it is A[d:1,d:1] where d=ncol(A). This conversion is needed if this package and VineCopula are used together.

Value

mxarray	array with M[k,j]= max A[k,1],..,A[k,j]
icomp	array with indicators for use in log-likelihood and simulation

See Also

vinearray

Examples

C= matrix(c(1,0,0,0,0, 1,2,0,0,0, 1,2,3,0,0, 1,2,3,4,0, 1,2,3,4,5), 5,5)
D= matrix(c(1,0,0,0,0, 1,2,0,0,0, 2,1,3,0,0, 3,2,1,4,0, 4,3,2,1,5), 5,5)
B0=matrix(c(1,0,0,0,0, 1,2,0,0,0, 1,2,3,0,0, 1,2,3,4,0, 1,3,2,4,5), 5,5)
B1=matrix(c(1,0,0,0,0, 1,2,0,0,0, 1,2,3,0,0, 1,2,3,4,0, 2,1,3,4,5), 5,5)
B2=matrix(c(1,0,0,0,0, 1,2,0,0,0, 2,1,3,0,0, 1,2,3,4,0, 1,2,3,4,5), 5,5)
B3=matrix(c(1,0,0,0,0, 1,2,0,0,0, 1,2,3,0,0, 1,3,2,4,0, 2,1,3,4,5), 5,5)
D6= matrix(c(1,0,0,0,0,0, 1,2,0,0,0,0, 2,1,3,0,0,0, 3,2,1,4,0,0, 4,3,2,1,5,0,
   5,4,3,2,1,6),6,6)
varray2M(C ,iprint=TRUE,"C ")
varray2M(D ,iprint=TRUE,"D ")
varray2M(B0,iprint=TRUE,"B0")
varray2M(B1,iprint=TRUE,"B1")
varray2M(B2,iprint=TRUE,"B2")
varray2M(B3,iprint=TRUE,"B3")
varray2M(D6,iprint=TRUE,"D6")

YafeiXu/CopulaModel documentation built on May 9, 2019, 11:07 p.m.