On Thu, Aug 6, 2009 at 16:43, Pierre GM<pgmdevlist@gmail.com> wrote:
On Aug 6, 2009, at 5:34 PM, Robert Kern wrote:
Every probability distribution can be generalized to accept a location and scale parameter even if their standard treatments do not.
pdf(x; loc,scale) -> pdf((x-loc)/scale)/scale
Agreed, as long as we are talking about *continuous* distributions. The behavior is quite different for *discrete* distributions. 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. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco