On 4/26/2007 12:48 PM, xpRt.wannabe wrote: > Dear List, > > Below is a simple, standard loss model that takes into account the > terms of an insurance policy: > > deductible <- 15 > coverage.limit <- 75 > insurance.threshold <- deductible + coverage.limit > > tmpf <- function() { > loss <- rlnorm(rpois(1, 3), 2, 5) > sum(ifelse(loss > insurance.threshold, loss - coverage.limit, > pmin(loss, deductible))) > } > net <- replicate(1000000, tmpf()) > > Now, I would like to enhance the model by incorporating the following > two probabilities: > > 1. Probability of claim being accepted by the insurance company, say, 0.8 > 2. Probability of payout by the insurance company, say, 0.999 > > Could anyone suggest how one might do this?
A general way to generate events with probability p is runif(n) < p. So I'd add n <- length(loss) accept <- runif(n) < 0.8 payout <- runif(n) < 0.999 and then require "accept & payout" before any payment at all, e.g. sum(ifelse(accept & payout, [ your old ifelse expression ], 0)) There are a lot of implicit independence assumptions here; they may not be very realistic. Duncan Murdoch ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.