simu.BB1 {Copula.surv} | R Documentation |
Simulating data from the BB1 copula
Description
n pairs of (U,V) are generated from the BB1 copula. n paris of (X,Y) are generated from the corresponding bivariate survival model with the Weibull marginal distributions. The default parameters (scale1=scale2=shape1=shape2=1) give the unit exponential distributions.
Usage
simu.BB1(n,alpha,d=0,scale1=1,scale2=1,shape1=1,shape2=1,Print=FALSE)
Arguments
n |
sample size |
alpha |
association (copula) parameter |
d |
BB1 copula's departure parameter from the Clayton (d=0 is the default) |
scale1 |
scale parameter for X |
scale2 |
scale parameter for Y |
shape1 |
shape parameter for X |
shape2 |
shape parameter for Y |
Print |
print Kendall's tau and means of X and Y if "TRUE" |
Details
See Section 2.6 of Emura et al.(2019) for copulas and bivariate survival times.
Value
U |
uniformly distributed on (0,1) |
V |
uniformly distributed on (0,1) |
X |
Weibull distributed (scale1, shape1) |
Y |
Weibull distributed (scale2, shape2) |
Author(s)
Takeshi Emura
References
Emura T, Lin CW, Wang W (2010) A goodness-of-fit test for Archimedean copula models in the presence of right censoring, Compt Stat Data Anal 54: 3033-43
Emura T, Matsui S, Rondeau V (2019), Survival Analysis with Correlated Endpoints, Joint Frailty-Copula Models, JSS Research Series in Statistics, Springer
Examples
n=100
Dat=simu.BB1(n=n,alpha=1,d=2,scale1=1,scale2=2,shape1=0.5,shape2=2)
plot(Dat[,"U"],Dat[,"V"])
cor(Dat[,"U"],Dat[,"V"],method="kendall")
plot(Dat[,"X"],Dat[,"Y"])
cor(Dat[,"X"],Dat[,"Y"],method="kendall")