|
- probability - Distribution of Event Times in a Poisson Process . . .
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?
- 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 normally distributed around the expected value and can take any real value, positive or negative, integer or fractional, whatever Finally, logistic regression only works for data that is 0-1-valued (TRUE-FALSE
- Derivation of the variance of the Poisson distribution
Is this derivation of the Poisson variance correct? I mainly want to make sure I'm applying the Law of the Unconscious Statistician (LOTUS) correctly $ Var[X] = E[X^2] - E[X]^2 $ $ = E[X^2] - \\
- 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 at work But you'd need to prove the existence of the poisson distribution AND the existence of an exponential pdf to show that a poisson process is a suitable model!
- Difference between Poisson and Binomial distributions.
If both the Poisson and Binomial distribution are discrete, then why do we need two different distributions?
- 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 really goo
- How does Poisson thinning work? - Mathematics Stack Exchange
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 equal 1, but otherwise it is a density)
- Why Specifically Use Poisson Regression For Count Data?
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 rather use a model in which predictions are always discrete (i e Poisson Regression) but to me, this seems like a formality
|
|
|