probability - Distribution of Event Times in a Poisson Process ...
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 …
Why is Poisson regression used for count data?
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 …
Relationship between poisson and exponential distribution
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 …
How to choose between poisson and binomial distributions
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. …
Poisson or quasi poisson in a regression with count data and ...
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 …
Residuals in poisson regression - Cross Validated
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 …
Why Specifically Use Poisson Regression For Count Data?
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 …
How to Choose Poisson Time Interval - Cross Validated
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 …
r - Rule of thumb for deciding between Poisson and negative …
Nov 6, 2023 · The Poisson model may estimate P too low, but I assume there's quite a few orders of magnitude to go before the interpretation changes (without considering any multiplicity or …
Poisson regression to estimate relative risk for binary outcomes
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 …