rbivcop2param: Bivariate 2-parameter copula families: simulation

In YafeiXu/CopulaModel: CopulaModel: Dependence Modeling with Copulas

Description

Bivariate 2-parameter copula families: simulation

Usage

rbb1(n,cpar,type="qcond",icheck=F)
rbb2(n,cpar,type="qcond",icheck=F)
rbb3(n,cpar,type="qcond",icheck=F)
rbb6(n,cpar,type="qcond",icheck=F)
rbb7(n,cpar,type="qcond",icheck=F)
rbb4(n,cpar,icheck=F)
rbb5(n,cpar,icheck=F)
rbb8(n,cpar,icheck=F)
rbb9(n,cpar,icheck=F)
rbb10(n,cpar,icheck=F)

Arguments

n	sample size
cpar	copula parameter: vector of length 2
type	"qcond" for conditional approach using C_{2|1}^{-1}; "mix" for stochastic representation based on mixture of max-id
icheck	flag to output means and estimated correlation of sample

Value

nx2 matrix with values in (0,1)

References

Joe H (1997). Multivariate Models and Dependence Concepts. Chapman & Hall.

See Also

rLTstochrep

Examples

n=500
set.seed(12345)
udat1=rbb1(n,c(.5,1.2),icheck=TRUE)
set.seed(12345)
udat2=rbb1(n,c(.5,1.2),type="mix",icheck=TRUE)
# another method based on Mittag-Leffler LT of the BB1 Archimedean copula
set.seed(12345)
udat3=rmbb1(n,2,c(.5,1.2))
print(summary(udat3))
print(cor(udat3)[1,2])

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