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 …

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 …

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 · I am trying to learn how to prove the following: if we know k k events occurred in a Poisson process between times t1 t 1 and t2 t 2, the exact times of these events are uniformly …

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 …

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.

Jun 26, 2015 · Poisson and exponential distributions are very strongly related but they're fundamentally different because the Poisson is discrete (a count variable) and the exponential …

Would like to know how confident I can be in my λ λ. Anyone know of a way to set upper and lower confidence levels for a Poisson distribution? Observations (n n) = 88 Sample mean (λ λ) …

May 22, 2016 · An important property of the Poisson random variable is that it may be used to approximate a binomial random variable when the binomial parameter n n is large and p p is …

Oct 19, 2024 · The Poisson process on $\mathbb {R}$ is called non-homogenous with rate $\lambda (t)$ if its intensity measure has density $\lambda (t)$ (total mass of which might not …