Thursday, March 09, 2006
Re: st: Producing random numbers from a kernel density
Peter Willem <firstname.lastname@example.org> asks:
> I am trying to draw random numbers from an arbitrary distribution. One idea > that occurred to me was to use a kernel density estimator (-kdensity-), but > I have no idea how to produce random numbers from the result. All > suggestions are welcome.
Look into something called "rejection sampling" which does not require the cumulative distribution function nor the ability to invert it to apply the probability integral transform. In fact, if you look up rejection sampling on wikipedia, the description there is good enough to go from there.
You will have to be able to evaluate your kernel density at any given point (not just at a grid), but at worst you just use linear interpolation between grid points.
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