Hi All, I would like to know if Numpy accepts addition of new distributions since the implementation of the Generator interface. If so, what is the criteria for a particular distribution to be accepted? The reason why i'm asking is because I would like to propose adding the Polya-gamma distribution to numpy, for the following reasons:
1) Polya-gamma random variables are commonly used as auxiliary variables during data augmentation in Bayesian sampling algorithms, which have wide-spread usage in Statistics and recently, Machine learning. 2) Since this distribution is mostly useful for random sampling, it since appropriate to have it in numpy and not projects like scipy [1]. 3) The only python/C++ implementation of the sampler available is licensed under GPLv3 which I believe limits copying into packages that choose to use a different license [2]. 4) Numpy's random API makes adding the distribution painless. I have done preliminary work on this by implementing the distribution sampler as decribed in [3]; see: https://github.com/numpy/numpy/compare/master...zoj613:polyagamma . There is a more efficient sampling algorithm described in a later paper [4], but I chose not to start with that one unless I know it is worth investing time in. I would appreciate your thoughts on this proposal. Regards, Zolisa Refs: [1] https://github.com/scipy/scipy/issues/11009 [2] https://github.com/slinderman/pypolyagamma [3] https://arxiv.org/pdf/1205.0310v1.pdf [4] https://arxiv.org/pdf/1405.0506.pdf Disclaimer - University of Cape Town This email is subject to UCT policies and email disclaimer published on our website at http://www.uct.ac.za/main/email-disclaimer or obtainable from +27 21 650 9111. If this email is not related to the business of UCT, it is sent by the sender in an individual capacity. Please report security incidents or abuse via https://csirt.uct.ac.za/page/report-an-incident.php.
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