[SciPy-dev] stats.distributions.poisson loc parameter : is it wise ?
Thu Aug 6 17:02:57 CDT 2009
On Aug 6, 2009, at 5:49 PM, Robert Kern wrote:
> On Thu, Aug 6, 2009 at 16:43, Pierre GM<email@example.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.
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