Hi,
> Use matrices modules to perform some basic operations for the
multivariate rv's, for example we could use the eigen module to perform
Principal Component Analysis and Factor Analysis.
This needs more thought and we should check for feasibility before moving
forward with PCA and FA.
> Add functions to calculate covariance and correlation matrices.
`covriance` function in `rv_interface.py` computes covariance between two
random variables. Computing covariance matrix can reuse `covariance`
function. Similar is the case for computing `correlation` matrices.
> Support symbolic expressions of density function that implement the
covariance matrix.
Can you provide some examples for this idea.
> Add sampling for multivariate distribution by using and extending upon
the numpy libraries.
I think we can do it. We can also look for other libraries as well. See the
framework for sampling univariate distributions currently present in
`master`.
> I also noticed that in the joint_rv_types for some classes there are
corresponding functions that return a JointRandomSymbol object with a call
to the multivariate_rv function buts that's not the case for other classes.
Is there a reason for it or it is something that has not yet been
implemented?
It would be easy to comment if you can give some examples.
Overall, we need to have more work planned for the summers as 40 hours per
week of requirement should be satisfied for passing the evaluations. Please
go through the following links,
1. https://github.com/sympy/sympy/wiki/GSoC-2020-Ideas#probability
2.
https://github.com/sympy/sympy/wiki/GSoC-2019-Report#ritesh-kumar-enhancement-of-statistics-module-francesco-bonazzi-sidhant-nagpal
3.
https://github.com/sympy/sympy/wiki/GSoC-2019-Report#gagandeep-singh-enhancement-of-statistics-module-francesco-bonazzi-sidhant-nagpal
4. https://github.com/sympy/sympy/wiki/GSoC-2020-Application-Template
Make sure that you satisfy the patch requirement for getting your proposal
evaluated.
On Fri, Mar 20, 2020 at 6:03 PM Basilis Kalos <[email protected]>
wrote:
> Hi!
> I am working on my application and i was thinking of ways to extend the
> support of multivariate distributions. For example:
> 1. Add more matrices support.
> a. Use matrices modules to perform some basic operations for
> the multivariate rv's, for example we could use the eigen module to
> perform
> Principal Component Analysis and Factor Analysis.
> b. Add functions to calculate covariance and correlation
> matrices.
> c. Support symbolic expressions of density function that
> implement the covariance matrix.
> 2. Add sampling for multivariate distribution by using and
> extending upon the numpy libraries.
> Does this sound good?
>
> I also noticed that in the joint_rv_types for some classes there are
> corresponding functions that return a JointRandomSymbol object with a call
> to the multivariate_rv function buts that's not the case for other classes.
> Is there a reason for it or it is something that has not yet been
> implemented?
>
> Thank you in advance!
>
> Τη Τρίτη, 17 Μαρτίου 2020 - 8:31:07 π.μ. UTC+2, ο χρήστης Gagandeep Singh
> (B17CS021) έγραψε:
>>
>> Hi,
>>
>> As far as I know, the "Probability" project is available for GSoC, 2020.
>> Please let me know of any questions regarding GSoC projects related to
>> `stats` module.
>>
>> Best wishes.
>>
>> On Tue, Mar 17, 2020 at 1:06 AM Basilis Kalos <[email protected]>
>> wrote:
>>
>>> Hi all
>>>
>>>
>>> The first project that i’m most interested to work on is the “Optimize
>>> floating point expressions”. I am familiar with Herbie and I have started
>>> reading its source code with the purpose of adapting ideas and even code
>>> (after re-writing it in python). How does that sound?
>>>
>>>
>>> I also would be really excited to work on the “Probability” project.
>>> Are any of those project ideas available? Should i look for projects that
>>> no-one else is working on?
>>>
>>>
>>> Thank you!
>>>
>>> --
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>>> .
>>>
>>
>>
>> --
>> With regards,
>> Gagandeep Singh
>> Github - https://github.com/czgdp1807/
>> Linkedin - https://www.linkedin.com/in/czgdp1807/
>> <https://www.linkedin.com/in/gdp1/>
>>
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> .
>
--
With regards,
Gagandeep Singh
Github - https://github.com/czgdp1807/
Linkedin - https://www.linkedin.com/in/czgdp1807/
<https://www.linkedin.com/in/gdp1/>
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