I can't imagine it should be that difficult, but probably, coming from Python, my mindset is biased.
I know I'm going to carry out 50 calculations and the result of each calculation, together with two parameters characterizing the calculation, should build up a data frame.
So my approach is to instantiate the data frame and then I want to add the results whenever they become available. Please see the indicated row below:
# Number of simulations
nsim = 50
# The data frame which should carry the calculation (parameters and solutions).
sol <- data.frame(col.names=c("ni", "Xbar", "n"))
# Fifty values for n.
n <- seq.int(5, 5000, length.out=nsim)
for(ni in n)
{
# A random sample containing possible duplicates.
X <- sample(seq(-ni, ni, length=ni+1), replace=T)
Xbar <- round(mean(X), 3)
sol <- rbind(sol, c(ni, Xbar, n)) # <<-- How to do this correctly??
}
This doesn't work.