Note, that a poisson distribution does not automatically imply an exponential pdf for waiting times between events. This only accounts for situations in which you know that a poisson process is …

I know of normality tests, but how do I test for "Poisson-ness"? I have sample of ~1000 non-negative integers, which I suspect are taken from a Poisson distribution, and I would like to …

I am looking for some information about the difference between binomial, negative binomial and Poisson regression and for which situations are these regression best fitted. Are there any …

Poisson distributed data is intrinsically integer-valued, which makes sense for count data. Ordinary Least Squares (OLS, which you call "linear regression") assumes that true values are …

How to calculate a confidence level for a Poisson distribution? Ask Question Asked 14 years, 2 months ago Modified 9 months ago

The quasi-Poisson likelihood model is a simple remedy for overdispersed count data because it introduces a dispersion parameter ($\phi$) into the Poisson model, so that the conditional …

Most birds produce no fledglings in a year, so there are many zero values in the data. With this in mind, I thought that a zero inflated poisson regression might be most appropriate. To test this …

Also, am I right in my understanding that "Poisson with parameter $\lambda$" is the same as saying that the expected number of events per unit time is $\lambda$? Then, is there a …

From Poisson regression, relative risks can be reported, which some have argued are easier to interpret compared with odds ratios, especially for frequent outcomes, and especially by …

Zuur 2013 Beginners Guide to GLM & GLMM suggests validating a Poisson regression by plotting Pearsons residuals against fitted values. Zuur states we shouldn't see the residuals …