Say I have a simulation that produces a single floating point number as a result, and a different number is produced each time the simulation runs. These numbers are randomly distributed according to some unknown distribution. I would like to approximate the underlying density distribution function based on a finite sample of numbers.
I know that I could use a histogram, but the size of the bins, which is essentially arbitrary, will significantly affect the results. I would like a way to do this which has no "arbitrariness".