[SciPy-User] scipy.stats.distributions.erlang - "boring" consensus building in a ticket
nicky van foreest
Sat May 5 16:59:52 CDT 2012
I just looked through the discussion in the ticket. Both sides (1: the
scale k should be an int, 2) allow k to be a float) make sense. From
my background in queueing I am inclined to say that k should be
restricted to the integers as in queueing theory the Erlang-k
distribution is used to model some distribution for which k can only
be an int. On the other hand, I am unsure whether a user of the Erlang
distribution should be protected from filling in a float. In all (?)
books on queueing and probability it is written that the Erlang
distribution is a special case of the gamma distribution, so users of
the Erlang distribution should know this (.... kind of, hopefully).
>From an implementation point of view I think that aliasing Erlang to
the gamma distribution makes good sense, and I don't believe that the
users or the Erlang distribution require to be protected against
filling in floats. Perhaps a sentence in the docstring of the Erlang
distribution that it is an alias of the gamma distribution, hence does
not check on the scale being an int, will prevent some potential
On 5 May 2012 22:20, <email@example.com> wrote:
> Should we restrict the shape parameter to be an integer instead of a float?
> Let's ask the users:
> Does anyone want an exception if the shape parameter is not an integer?
> Is there a demand or use case for estimating the shape parameter as an
> integer instead of a float?
> right now erlang and gamma are essentially the same, as far as I can see
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