R/simCNVdataWeibull.R

In isglobal-brge/CNVassoc: Association analysis of CNVs and imputed SNPs incorporating uncertainty

simCNVdataWeibull <- function(n, mu.surrog, 
        sd.surrog, w, lambda, shape, time.cens = Inf, 
        cnv.random = FALSE) {
        scale <- lambda^(-1/shape)
        w <- w/sum(w)
        k <- length(mu.surrog)
        if (length(shape) == 1) 
            shape <- rep(shape, k)
        if (length(scale) == 1) 
            scale <- rep(scale, k)
        if (cnv.random) {
            nj <- rmultinom(n = 1, size = n, 
                prob = w)
        } else {
            nj <- round(n * w)
            nj[1] <- nj[1] + n - sum(nj)
        }
        surrog <- unlist(lapply(seq(along = nj), 
            function(j) rnorm(nj[j], mean = mu.surrog[j], 
                sd = sd.surrog[j])))
        cnv <- rep(seq_len(k), nj)
        resp <- unlist(lapply(seq(1,k), function(j) rweibull(nj[j], 
            shape[j], scale[j])))
        cens <- ifelse(resp > time.cens, 0, 1)
        resp <- ifelse(resp > time.cens, time.cens, 
            resp)
        out <- data.frame(resp, cens, cnv, surrog)
        out <- out[sample(seq_len(n)), ]
        out
}