# [R] Ifelse leading to inconsistent result

peter dalgaard pdalgd at gmail.com
Wed Jun 26 18:59:17 CEST 2013

```On Jun 26, 2013, at 17:40 , Neville O'Reilly wrote:

> I have used ifelse in count variables to count the number of times in a simulation the values of a vector of logprice fall within mutually exclusive ranges. However, there is a double count in the result i.e. i am getting output indicating values falling in mutually exclusive ranges. Here is the code and result
> R script

Don't use ifelse, it just confuses the logic.

As far as I can tell, the code is equivalent (except for integer conversion) to

CountLoss[i] <- (minlogP < log(950000)) | (maxlogP <= log (1000000))
CountProf[i] <- (maxlogP >= log (1100000))

and that doesn't look mutually exclusive to me.

> niter = 1e5 # number of iterations is 10^5
> CountLoss = rep(0,niter)
> CountProf = rep (0,niter)
> set.seed(2009) # enables reproducibility of result if script run again"
> for (i in 1:niter)
> {
>  r = rnorm(100,mean=.05/253,
>            sd=.23/sqrt(253)) # generate 100 random normal numbers
>  logPrice = log(1e6) + cumsum(r) #vector of 100 days log prices
>  maxlogP = max(logPrice) # max price over next 100 days
>  minlogP = min(logPrice)
>  CountLoss[i] <- ifelse (minlogP < log(950000), 1, ifelse (maxlogP > log (1000000), 0, 1))
>  CountProf[i] <- ifelse (maxlogP < log (1100000),0,1)
> }
> sum(CountLoss)
> mean(CountLoss) # fraction of times out of niter that stock is sold for a loss in a 100 day period
> sum(CountProf)
> mean(CountProf) # fraction of times out of niter that stock is sold for a profit in a 100 day period
>
> Output
> sum(CountLoss)
> [1] 64246
>> mean(CountLoss) # fraction of times out of niter that stock is sold for a loss in a 100 day period
> [1] 0.64246
>> sum(CountProf)
> [1] 51857
>> mean(CountProf) # fraction of times out of niter that stock is sold for a profit in a 100 day period
> [1] 0.51857
>
> CountLoss and CountProf should sum to less than the number of interations. When I troubleshoot by reducing the number of iterations and that size of the logprice, I can't reproduce the contradicion.
>
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