[SciPy-dev] stats.distributions.poisson loc parameter : is it wise ?

[Pierre GM]

On Aug 6, 2009, at 5:49 PM, Robert Kern wrote:

> On Thu, Aug 6, 2009 at 16:43, Pierre GM<pgmdevlist at gmail.com> wrote:
>> Even if
>> the scale is simply discarded already, using a location will probably
>> NOT give the expected result
>
> It depends on what your expectations are. For the discrete
> distributions, all the loc parameter means is this, as documented:
>
>  pmf(x; loc) -> pmf(x-loc)
>
> That's it. I don't know why you would expect anything else.

Because using a location parameter, you change the support domain.  
Back to the example of a Poisson distribution with loc=1, the support  
domain is now x>=1, which amounts to truncating the zeroes. The mean  
of a zero-truncated Poisson with parameter pr should be pr/(1-exp(- 
pr)), but we end up with pr+1. Not the expected result.
I think it's a source of confusion to keep a location parameter for  
discrete distributions. it'd be worth to implement method to allow  
truncation, but just a loc parameter doesn't do it.