rfactcop: Simulation for copula models with factor structure

In vincenzocoia/CopulaModel: CopulaModel: Dependence Modeling with Copulas

Description

Simulation for copula models with factor structure, with links to C code

Usage

r1fact(n,d,cpar,copcode)
r2fact(n,d,cpar,copcode)
rbifact(n,grsize,cpar,copcode)
rnestfact(n,grsize,cpar,copcode)

Arguments

n	sample size
d	number of variables
cpar	copula parameter vector
grsize	vector of group sizes for mgrp groups with sum(grsize)=d
copcode	current options are 1 for Gaussian, 2 for t, 3 for Gumbel, -3 for reflected Gumbel, 5 for Frank; 9 for BB1 1-factor, 9 for BB1/Frank 2-factor and bi-factor; 11 for Gumbel/BB1 nested factor

Details

These do simulations via C code; currently there are not as many possible options compared with sim1fact(), sim2fact(), simbifact() and simnestfact()

Value

nxd matrix of d dependent U(0,1) variables

See Also

factorcopsim structcop

Examples

 
set.seed(123)
rhvec=c(.8,.7,.6,.5,.5)
udat1=r1fact(3,5,rhvec,1); print(udat1)
udat2=r1fact(3,5,c(rhvec,4),2); print(udat2)
cpar1=seq(1.1,1.5,.1)
udat3=r1fact(3,5,cpar1,3); print(udat3)
cparbb1=c(.2,1.1,.2,1.2,.2,1.3,.2,1.4,.2,1.5)
udat9=r1fact(3,5,cparbb1,9); print(udat9)
#
set.seed(123)
cpar2=c(seq(1.1,1.5,.1),rep(1.1,5))
udat3=r2fact(3,5,cpar2,3); print(udat3)
cpar2bb1=c(cparbb1,seq(1.1,1.5,.1))
udat9=r2fact(3,5,cpar2bb1,9); print(udat9)
#
grsize=c(2,2,2)
set.seed(123)
cparbi=c(seq(1.1,1.6,.1),rep(1.1,6))
udat3=rbifact(3,grsize,cparbi,3); print(udat3)
cparbibb1=c(cparbb1,.2,1.6,seq(1.1,1.6,.1))
udat9=rbifact(3,grsize,cparbibb1,9); print(udat9)
#
grsize=c(2,2,2)
set.seed(123)
cparne=c(rep(1.1,3),seq(1.1,1.6,.1))
udat3=rnestfact(3,grsize,cparne,3); print(udat3)
cparnebb1=c(seq(0.6,1.1,.1),cparbb1)
udat9=rnestfact(3,grsize,cparnebb1,9); print(udat9)

vincenzocoia/CopulaModel documentation built on Oct. 27, 2021, 6:41 a.m.