# [R] A coding question involving variable assignments in ifelse()

Duncan Murdoch murdoch at stats.uwo.ca
Thu Apr 26 20:45:08 CEST 2007

```On 4/26/2007 2:31 PM, xpRt.wannabe wrote:
> Just to be sure, is what I have below the right intepretation of your
> suggestion:

Yes, that's what I suggested.

Duncan Murdoch

> deductible <- 15
> coverage.limit <- 75
> insurance.threshold <- deductible + coverage.limit
>
> tmpf <- function() {
> loss <- rlnorm(rpois(1, 3), 2, 5)
> n <- length(loss)
> accept <- runif(n) < 0.8
> payout <- runif(n) < 0.999
> sum(ifelse(accept & payout, ifelse(loss > insurance.threshold, loss -
> coverage.limit, pmin(loss, deductible)), 0))
> }
> net <- replicate(1000000, tmpf())
>
> On 4/26/07, Duncan Murdoch <murdoch at stats.uwo.ca> wrote:
>> 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
>>
>> 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
>>
>
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