### Example:
### First simulate a sample of 10 individuals (for more details see the help of \code{simreccomp})
N <- 10
dist.x <- c("binomial", "normal")
par.x <- list(0.5, c(0, 1))
beta.xr <- c(0.3, 0.2)
beta.xc <- c(0.5, 0.25)
dist.zr <- "gamma"
par.zr <- 0.25
dist.zc <- "gamma"
par.zc <- 0.3
dist.rec <- "weibull"
par.rec <- c(1, 2)
dist.comp <- "weibull"
par.comp <- c(1, 2)
fu.min <- 2
fu.max <- 2
cens.prob <- 0.2
dfree <- 30 / 365
pfree <- 0.5
simdata <- simreccomp(
N = N, fu.min = fu.min, fu.max = fu.max, cens.prob = cens.prob,
dist.x = dist.x, par.x = par.x, beta.xr = beta.xr, beta.xc = beta.xc,
dist.zr = dist.zr, par.zr = par.zr, dist.zc = dist.zc, par.zc = par.zc,
dist.rec = dist.rec, par.rec = par.rec, dist.comp = dist.comp, par.comp = par.comp,
pfree = pfree, dfree = dfree
)
simreccompPlot(simdata)
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