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

[xpRt.wannabe]

Is this an ad hominem comment or a comment of brevity?  Unless my eyes
are playing tricks on me, I can't seem to find any language in the
Posting Guide on what is considered a reasonable vs. unreasonable
request from an anonymous poster.  Kindly point me to it if it exists.

In any case, thanks for your time and suggestion.

On 4/26/07, Duncan Murdoch <murdoch at stats.uwo.ca> wrote:
> On 4/26/2007 5:21 PM, xpRt.wannabe wrote:
> > I made a few slight modifications to the original model in an effort
> > to see the inner workings of the code:
> >
> > deductible <- 1
> > coverage.limit <- 2
> > insurance.threshold <- deductible + coverage.limit
> >
> > <snip>
> >
> > set.seed(123)
> > loss <- abs(rnorm(rpois(1, 5), 1, 3))
> > 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))
> >
> > [1] 6.188817
> >
> > <snip>
> >
> > To tease out the data as well as to see the effect of 'accept &
> > payout', I did the following:
> >
> >> loss
> > [1] 3.401663 4.570620 4.068667 4.718488
> >> accept
> > [1]  TRUE FALSE  TRUE  TRUE  # The second loss claim is NOT accepted
> > by the insurance company.
> >> payout
> > [1] TRUE TRUE TRUE TRUE
> >> accept & payout
> > [1]  TRUE FALSE  TRUE  TRUE  # The second entry is FALSE because of
> > the second entry in 'accept.'
> >
> > Based on the inner ifelse() expression, the original loss numbers
> > become : 1.401663, 2.570620, 2.068667, 2.718488, respectively (which
> > is fine and what I wanted).
> >
> > Because the second entry in 'accept & payout' is FALSE, the second
> > altered loss number (2.570620) becomes 0, making sum(...) equal
> > 6.188817.  Unfortunately this is _not_ what I want, and I apologize
> > for not being clear in the first place.  What I want is: for any FALSE
> > entry, the original loss number is unaltered, as opposed to become 0.
> > So in the example above, the four numbers that should have been added
> > are: 1.401663, 4.570620, 2.068667, 2.718488, yielding 10.759438
> > instead of 6.188817.
> >
> > Any further suggestions would be greatly appreciated.
>
> I'm sorry, but from an anonymous poster that's not a reasonable request.
>  Just work it out yourself.
>
> Duncan Murdoch
>
> >
> > On 4/26/07, Duncan Murdoch <murdoch at stats.uwo.ca> wrote:
> >> 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
> >>>> 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 at 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.
> >>
>
>