bution."
That leaves open "MultivariateXxDistribution" which we could add later.
Assuming there are no objections to this approach, it would be great
if you could create a JIRA for this and attach a patch taking a stab
at it.
Phil
>
> Christian
>
> --
> View this message i
(e.g. if a multidimension
normal distribution shall be implemented).
Christian
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nuous (by that, I mean
> real-valued RV) case. Note how it is overriden now in
> AbstractIntegerDistribution. So why not just leave that alone and
> separate out the discrete/integer/whatever-we-want-to-call-it case?
> Discrete distributions are fundamentally different. They
>
> What exactly do we gain by having the common parent? The inverse
> cdf machinery will work only for the continuous (by that, I mean
> real-valued RV) case. Note how it is overriden now in
> AbstractIntegerDistribution. So why not just leave that alone and
> separate out the discrete/integer/
k differently. Why not just cleanly separate?
Phil
>
> In my opinion, we benefit from having one such common ancestor instead
> of two "independent" linages.
>
>> Phil
>>> Christian
>>>
>>> --
>>> View this message in context:
>&
to
make this generic parameterising the argument to cdf and others.
In my opinion, we benefit from having one such common ancestor instead
of two "independent" linages.
>
> Phil
>>
>> Christian
>>
>> --
On Mon, Oct 31, 2011 at 2:56 PM, cwinter wrote:
>
> Phil Steitz wrote:
> >
> > Maybe it would be best to eliminate IntegerDistribution then and
> > merge Distribution and ContinuousDistribution, so we have two roots
> > - DiscreteDistribution and ContinuousDistribution. The only reason
> > real
f the distribution. Apart
from this, a separate interface for more general discrete distributions is
indeed not required.
Christian
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istribution as a parent, so why not just drop both
IntegerDistribution and Distribution and move to two roots with
doubles / ints as domains and contracts cleaned up to deal with
discrete vs continuous cases consistently.
Phil
>
> Christian
>
> --
> View this message in con
ty interface. Thus there is in fact the
question whether it should be eliminated. Otherwise it would be just a
"flag" for discrete distributions and that's indeed independent of the
sample space.
Christian
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e value in
supporting discrete distributions over sample spaces that are not
embedded in the integers.
Phil
>
> Best Regards,
> Christian
>
>
> --
> View this message in context:
> http://apache-commons.680414.n4.nabble.com/math-Distributions-over-sample-spaces-
eDistribution.
Best Regards,
Christian
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ian
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On Sun, Oct 23, 2011 at 6:50 PM, Phil Steitz wrote:
> On 10/23/11 4:36 PM, Ted Dunning wrote:
> > I think it isn't much to worry about forcing all the current stuff into
> an
> > unnatural structure for use cases that are not particularly common.
> >
> > The cases that I have seen for distributio
On 10/23/11 4:36 PM, Ted Dunning wrote:
> I think it isn't much to worry about forcing all the current stuff into an
> unnatural structure for use cases that are not particularly common.
>
> The cases that I have seen for distributions over non-reals are permutations
> and graphs. In neither case
I think it isn't much to worry about forcing all the current stuff into an
unnatural structure for use cases that are not particularly common.
The cases that I have seen for distributions over non-reals are permutations
and graphs. In neither case did I feel an urge to file a bug against
java.lan
Comments on [math-692] have made me curious about how might we run
into discrete distributions that do not extend
AbstractIntegerDistribution in practical applications. Does anyone
have the need for this? One reason that I am asking about this is
that I have always felt a little funny about basic
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