Sep 18, 2019 · This is because the CDF of Poisson distribution is related to that of a Gamma distribution. Hence the incomplete gamma function.

Sep 5, 2024 · Normally, everyone talks about the distribution of interarrival times in a Poisson Process are Exponential ... but what about the distribution of the actual event times?

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 at …

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 normally distributed …

May 17, 2014 · 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 …

I have count data (demand/offer analysis with counting number of customers, depending on - possibly - many factors). I tried a linear regression with normal errors, but my QQ-plot is not really goo...

The Poisson distribution is easier to work with than the binomial distribution. It is easier to compute the pdf and especially the cdf. Its generating functions have nice properties. Etc. Second, in applications, …

Aug 25, 2021 · There are different types of continuous extensions of Poisson distribution. I favor the one presented in this paper: "Continuous counterparts of Poisson and binomial distributions and their …

Oct 23, 2020 · A Poisson process is one where mean = var = λ. How do you decide what time interval fulfills these criteria when fitting the Poisson distribution to a process? Can all processes be modeled …

Sep 8, 2022 · Why should Poisson Regression be used for Count Data instead of a "vanilla linear regression"? I understand the basic argument : Count Data is by definition discrete and you would …