Alan G Isaac wrote:
I would think that
multinomial(1,prob,size=ntrials).sum(axis=0)
would be equivalent to
multinomial(ntrials,prob)
but the first gives a surprising result. (See below.)
Explanation?
On Wed, 05 Dec 2007, Robert Kern apparently wrote:
Pretty much anyone who
I would think that
multinomial(1,prob,size=ntrials).sum(axis=0)
would be equivalent to
multinomial(ntrials,prob)
but the first gives a surprising result. (See below.)
Explanation?
Thank you,
Alan Isaac
ntrials = 10
prob = N.arange(100,dtype=N.float32)/4950
Alan G Isaac wrote:
I would think that
multinomial(1,prob,size=ntrials).sum(axis=0)
would be equivalent to
multinomial(ntrials,prob)
but the first gives a surprising result. (See below.)
Explanation?
A bug in rk_binomial_inversion(). Unfortunately, this looks like a logical bug
in
Alan G Isaac wrote:
I would think that
multinomial(1,prob,size=ntrials).sum(axis=0)
would be equivalent to
multinomial(ntrials,prob)
but the first gives a surprising result. (See below.)
Explanation?
Pretty much anyone who derives their binomial distribution algorithm from
