[R] Ifelse leading to inconsistent result

[David Carlson]

I don't see that you have set up mutually exclusive ranges. If we
modify your code so save the maxlogP and minlogP values:

niter = 1e5 # number of iterations is 10^5
CountLoss = rep(0,niter)
CountProf = rep (0,niter)
maxlogP <- rep(0, ninter)
minlogP <- rep(0, ninter)
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[i] = max(logPrice) # max price over next 100 days
  minlogP[i] = min(logPrice)
  CountLoss[i] <- ifelse (minlogP[i] < log(950000), 1, ifelse
(maxlogP[i] > log (1000000), 0, 1))
  CountProf[i] <- ifelse (maxlogP[i] < log (1100000),0,1)
}
both <- which(CountLoss+CountProf>1)
length(both)
# 18484
head(both)
# [1]  1  5  9 12 15 25
ifelse (minlogP[1] < log(950000), 1, ifelse (maxlogP[1] > log
(1000000), 0, 1))
# [1] 1
ifelse (maxlogP[1] < log(1100000),0,1)
# [1] 1
exp(maxlogP[1])
# [1] 1204589
exp(minlogP[1])
# [1] 932747.5

Your first simulation meets both criteria along 18483 others!

-------------------------------------
David L Carlson
Associate Professor of Anthropology
Texas A&M University
College Station, TX 77840-4352

-----Original Message-----
From: r-help-bounces at r-project.org
[mailto:r-help-bounces at r-project.org] On Behalf Of Neville O'Reilly
Sent: Wednesday, June 26, 2013 10:41 AM
To: r-help at r-project.org
Subject: [R] Ifelse leading to inconsistent result

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
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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