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From Mikkel Meyer Andersen <m...@mikl.dk>
Subject Re: [math] Generate random data using the Inverse CDF Method?
Date Tue, 27 Oct 2009 00:11:16 GMT
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.steitz@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.steitz@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?
>>>
>>
>>
>>
>
>
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