"culpritNr1" wrote
I tried the scipy function. I don't understand it.
Try reading about it here:
http://numpy.sourceforge.net/numdoc/HTML/numdoc.htm
It explains the output format. I believe it applies to the scipy
version as well as the numpy.
The python documentation on this functionali
I just figured it out myself.
This is how to do it both the naive and the efficient way, respectively:
>>> import math
>>> from scipy import factorial
>>> lam = 1
>>> k = 2
>>> math.exp(-lam) * lam**k / factorial(k)
0.18393972058572117
>>> from scipy import stats
>>> stats.poisson.pmf(2,1)
arra
On Tue, Jan 13, 2009 at 5:11 PM, culpritNr1 wrote:
>
> Hi Jarvis,
>
> I tried the scipy function. I don't understand it. Look, if you go to
> http://en.wikipedia.org/wiki/Poisson_Distribution wiki's Poisson
> distribution documentation you'll find that this is the naive way to
> compute a Poisson
Hi Jarvis,
I tried the scipy function. I don't understand it. Look, if you go to
http://en.wikipedia.org/wiki/Poisson_Distribution wiki's Poisson
distribution documentation you'll find that this is the naive way to
compute a Poisson probability mass function
>>> lam = 1
>>> k = 2
>>> math.exp(
On Wed, Jan 14, 2009 at 8:27 AM, culpritNr1 wrote:
>
>
> there some kind of random.poisson()?
>
> Thank you,
>
> culpritNr1
>
> Hello try the scipy library:
>>> from scipy import stats
>>> lamb = 10
>>> stats.distributions.poisson.rvs(lamb, loc=0)
array([5])
>>> stats.distributions.poisson.rvs(la
Hello All,
OK. This time a less trivial question.
Is there a function to enable us sample from a Poisson distribution?
There is random.uniform, random.normalvariate(), random.expovariate()... Is
there some kind of random.poisson()?
Thank you,
culpritNr1
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