I want perform monte-carlo simulations for 12 iterations with mean varying from 5 to 60 by an interval of 5. As an output of the following code I want each simulation result in a different columns as a data frame. For instance, if I want to perform 10,000 simulations for each set of mean and std.dev, the resultant dataframe will have 12 columns and 10000 rows. The code is:
df<-data.frame()
for (i=5; i<=60; i=i+5)
{
{
cvsq=1
mcs=rnorm(10000,i,(i*cvsq))
op$i<-data.frame(mcs)
}
df<-cbind(op)
}
df
The results from this code is a data frame with two columns with simulation results for 60 and 5 only.
Can use lapply and do.call
DF <- do.call(cbind,
lapply(seq(5,60,5), function(i) setNames(data.frame(rnorm(10000, i, (i*cvsq))), i))
)
head(DF)
5 10 15 20 25 30 35 40 45 50 55 60
1 2.621 9.3083 7.004 -20.4034 43.77 -6.906 15.68 60.42 -30.981 55.634 -2.329 156.45
2 3.490 -4.1331 9.461 24.7668 15.06 69.660 15.48 132.71 21.109 8.984 84.382 63.27
3 4.863 -0.8772 3.649 0.2247 14.01 16.365 81.56 -19.01 27.993 15.910 13.690 106.21
4 4.516 17.0948 -2.754 9.7998 37.01 76.459 56.19 26.39 80.759 54.173 13.152 34.03
5 11.110 16.7807 39.529 -2.9710 -11.61 -10.982 68.50 48.68 53.811 30.779 78.196 -36.90
6 -3.297 1.0127 15.150 37.9734 11.31 45.855 58.18 22.91 5.654 66.101 -35.472 68.05