Chia C Chong <[EMAIL PROTECTED]> wrote in message acro4s$72c$[EMAIL PROTECTED]">news:acro4s$72c$[EMAIL PROTECTED]... > I have a random variable,X with 1000 samples (all discrete values). I want > to test whether X can sastify a Poisson process or not. How should I test > it?
I assume you mean that you have one sample with 1000 observations. Firstly, I want to caution you against using hypothesis tests for goodness of fit of distributions in general. Usually it turns out that hypothesis tests aren't actually what is needed for the problem at hand (which you don't specify), so be sure that it's really a hypothesis test that is what's required to answer your underlying question of interest! (To begin with, we already know the answer - the distribution from which the data comes is not precisely Poisson, so the real question must be somewhat different. Often, for example, the question of interest is more along the lines of "How badly will my results be affected by the fact that the data doesn't exactly come from a Poisson distribution?". That question /isn't/ answered by hypothesis tests at all. There are some questions for which hypothesis tests are a reasonable answer, it's just that people are not usually trying to get answers to those questions.) As for how to test it, it depends on what your alternatives are. For example, if you want to test it against some overdispersed model that the Poisson might be a special case of, you do something different than if you're interested in testing against a general discrete alternative on the non-negative integers. Glen . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
