As I e-mailed Matt just now, I think this is a great idea. I will most 
likely start with the symbolic construction of Markov Chains and work from 
there.
-Chase

On Tuesday, March 4, 2014 9:02:55 AM UTC-8, F. B. wrote:
>
>
>
> On Tuesday, March 4, 2014 6:18:18 AM UTC+1, Chase Relock wrote:
>>
>> I was looking at SymPy's matrix code and was curious if that supports 
>> symbolic computation right now or is it only numeric?
>>
>
> Of course you can put symbols inside sympy matrices (if that is what you 
> mean), for numeric-only ones, have a look at numpy (technically numpy could 
> be forced to use symbols, but it's not straightforward).
>  
>
>> As for some of the individual pieces, I think the following are important 
>> concepts needed in financial statistics that I am unsure SymPy currently 
>> has functionality for:
>> kernel density estimators for PDFs
>> Empirical distribution functions
>> Statistical moments
>> Stochastic Processes
>> Stochastic/Ito Calculus
>> Time series
>> Matrix decomposition (spectral, singular value)
>>
>>
> What about introducing stochastic processes, Martingales and Ito 
> integration (all in symbolic representation, of course)? I think that could 
> already be a good project.
>
> By the way, I have been using the sympy.stats module, and I get a lot of 
> *NotImplementedError*, and other kinds of errors. Finishing that parts 
> would be great, too.
>

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