R help - Apr 2007 - A coding question involving variable assignments in ifelse()

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?


platform i386-pc-mingw32
arch     i386
os       mingw32
system   i386, mingw32
status
major    2
minor    2.1
year     2005
month    12
day      20
svn rev  36812
language R

Thanks,

Another similar way to do this using apply is:

apply(ar1==ar2,1,all)

Best,
Finny Kuruvilla

*****************************************************************
Finny Kuruvilla, MD, PhD
Harvard Medical School Fellowship Program in Transfusion Medicine
Broad Institute of MIT and Harvard
Homepage: http://www.people.fas.harvard.edu/~kuruvill/home/
> Estimated people,
> 
> I have two matrices:
> 
> ar1 <- array(data=c(1:16),dim=c(4,4))
> ar2 <- array(data=c(1,2,3,3,5:16),dim=c(4,4))
> 
> They only differ in the fourth row. I would like to compare them in
> order to know which columns are equal.
> 
> The following works, but I would like to have a better solution, and
> not
> to use what someone called "prehistorical loops":
> 
> for(i in c(1:4)) { cat(as.character(i),": ",
> as.character(setequal(ar1[i,],ar2[i,])), "\n") }
> 1 :  TRUE
> 2 :  TRUE
> 3 :  TRUE
> 4 :  FALSE
> 
> I cannot devise how to use the apply function for this.
> Thanks a lot,
> Federico

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

I think Duncan's suggestion that the poster work it out for
him/her self is perfectly reasonable.  People can be anonymous
all they like.  Those of us who are made suspicious by this
anonymity (what have they got to hide?) can decline to provide
assistance.

				cheers,

					Rolf Turner
					rolf at math.unb.ca