<div dir="auto">This is in the pending PR.  Hopefully out in 1.20.  <div dir="auto"><br></div><div dir="auto">Kevin</div><div dir="auto"><br></div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Sun, Nov 1, 2020, 23:55 Currurant <<a href="mailto:currurant@gmail.com">currurant@gmail.com</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">I realized that neither numpy.random.multinomial nor rng.multinomial has the<br>
ability to draw from different multinomial distributions at the same time<br>
like what MATLAB mnrnd() does here: <br>
<br>
<a href="https://www.mathworks.com/help/stats/mnrnd.html" rel="noreferrer noreferrer" target="_blank">https://www.mathworks.com/help/stats/mnrnd.html</a><br>
<br>
Also, I have asked this question on StackOverFlow:<br>
<br>
<a href="https://stackoverflow.com/questions/64529620/is-there-an-efficient-way-to-generate-multinomial-random-variables-in-parallel?noredirect=1#comment114131565_64529620" rel="noreferrer noreferrer" target="_blank">https://stackoverflow.com/questions/64529620/is-there-an-efficient-way-to-generate-multinomial-random-variables-in-parallel?noredirect=1#comment114131565_64529620</a><br>
<br>
It seems like this is something good to add to numpy.random, since it would<br>
be much more faster when you have many multinomial distributions to draw<br>
from---using loops.<br>
<br>
<br>
<br>
--<br>
Sent from: <a href="http://numpy-discussion.10968.n7.nabble.com/" rel="noreferrer noreferrer" target="_blank">http://numpy-discussion.10968.n7.nabble.com/</a><br>
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</blockquote></div>