06-08-2016 10:30 PM
I believe that is using the CDF, cumulative distribution function.
06-09-2016 06:41 AM
If you have an observed value of some test statistics that follows a Poisson distribution, then Reeza is correct and you can use the CDF function:
OneSidePVal = 1 - cdf("Poisson", ObsValue, lambda);
However, since most statistics do not follow a Poisson distribution, maybe you are asking about fitting a Poisson distribution to data and obtaining a p-value for the goodness-of-fit test? In that case, you should use PROC GENMOD to fit the distribution as shown in the article "Fitting a Poisson distribution to data in SAS". (You can also use COUNTREG.)
Unfortunately, the statistics that come out of PROC GENMOD do not include p-values, but you can use PROC FREQ to compute a chi-square statistics that compares the observed and expected values in each category. The details are shown in the article "Testing the fit of a discrete distribution." If you are interested, there are also graphical techniques for evaluating the fit.
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