Ted, sorry hadn't seen your e-mail before sending mine. Yes, I agree in you point of having specialised good algorithms. But in lack of such methods, I'd prefer being able to have a general method, although it might be bad compared to a specialised one.
2009/10/27 Phil Steitz <phil.ste...@gmail.com>: > Ted Dunning wrote: >> Inverse CDF methods work for discrete distributions as well as continuous >> ones. > > Thanks. That's what I was missing. I would still rather see the > implementations in the random package and for common distributions, > e.g. Poisson, pick a method that is well-suited for the distribution. > > Phil >> >> On Mon, Oct 26, 2009 at 4:50 PM, Phil Steitz <phil.ste...@gmail.com> wrote: >> >>>> If not, I would create a public interface >>>> DistributionWithInverseCumulativeProbability (who has a better name?) >>>> with the method inverseCumulativeProbability (right now it's on >>>> ContinuousDistribution and some other subclasses and don't seem to be >>>> gathered in an interface) and all the distributions with the >>>> inverseCumulativeProbability-method should implement this interface. >>> I am not following you here. What exactly is the difference between >>> DistributionWithInverseCumulativeProbability and >>> ContinuousDistribution? >>> >> >> >> > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org > For additional commands, e-mail: dev-h...@commons.apache.org > > --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org
