On Fri, Nov 18, 2011 at 2:19 PM, Matthew Rocklin <[email protected]> wrote:
> Yes. Discrete random variables in full generality (i.e. both finite and
> infinite cases) have not been implemented. There is, for example, no Poisson
> random variable.
> When I looked into writing infinite sets and infinite discrete random
> variables I came to the conclusion that solving this problem in full
> generality was very difficult/impossible. An implementation to solve
> uni-variate infinite RV problems is feasible but when you start mixing
> multiple variables (i.e. conditions on both chickens and pigs) them you
> quickly produce provably difficult problems.
> Sorry for the thread hijack.

Can you at least give an algorithm that uses steps that can be done at
least some of the time.  For example, if a step is "solve this system
of equations," then obviously sometimes you won't be albe to do it,
but you can at least some of the time, and for those cases, it would
be useful to get the solution.

Or is it more complicated than that?

Aaron Meurer

>
> On Fri, Nov 18, 2011 at 12:59 PM, Aaron Meurer <[email protected]> wrote:
>>
>> On Fri, Nov 18, 2011 at 10:29 AM, Matthew Rocklin <[email protected]>
>> wrote:
>> >> This is a neat example.  Does this first one also just use for loops,
>> >> or does it solve the equations?
>> >>
>> >> Aaron Meurer
>> >>
>> >
>> > The finite random variable code is just a syntactically nice way to set
>> > up
>> > and go though large iterators asking questions. It's not computationally
>> > clever in any way.
>> >
>>
>> I see. So it would not be possible to extend the result to an infinite
>> set (which hopefully has a finite solution).  In other words, you have
>> to know ahead of time how many sides to put on your Die.
>>
>> Aaron Meurer
>>
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