> I've made a function that executes a monte-carlo simulation. > It always needs a lot of time until e.g. 1Mio simulation steps are done. > So I would like to know, how many percent of the work is already done.
This reminds me of my 'iterator' class I was working on - but never really finished.
Instead of doing:
for(i in 1:10000000){
dostuff(i)
}which creates a vector of c(1,2,...,10000000), you create an iterator object, and do a while loop:
myLoop = loop(N=10000000)
while(iterate(myLoop)){
dostuff(iteration(myLoop))
}now all the information about the loop is encapsulated in the iterator object 'myLoop', and there are methods for working out when the loop might finish:
predictEnd(myLoop)
Predicted finish at 12-Dec-02 12:12:34
I also started work on a superclass of this for MCMC runs, where you could specify a burn-in period and a sampling thinning parameter, and then there were methods for telling if you were in the burn-in period or if this was an interation that you were sampling in your output.
Maybe I'll have a go at cleaning this all up over the easter break and making a proper package of it.
Baz
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