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- Interarrival Times for a Non-Homogeneous Poisson Process
It is well known that the interarrival times for a standard (i e homogeneous) Poisson Process follow an Exponential Distribution (What is the correct inter-arrival time distribution in a Poisson p
- Relationship between poisson and exponential distribution
Exponential pdf can be used to model waiting times between any two successive poisson hits while poisson models the probability of number of hits Poisson is discrete while exponential is continuous distribution It would be interesting to see a real life example where the two come into play at the same time $\endgroup$ –
- r - Rule of thumb for deciding between Poisson and negative binomal . . .
I'm not sure how one would compare the Poisson vs NB models using the score test, however In the worked model, the t test of poi_glm gives p=4 6e-9 If I use glm nb to analyze the same data, I get a t test p=2 5e-8 I'm not sure how to compare these If I run a two-sample t test on the NB vs Poisson z values, I get p=0 90 )
- 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
- How to calculate a confidence level for a Poisson distribution?
This confidence interval is "efficient" in the sense that it comes from maximum likelihood estimation on the natural parameter (log) scale for Poisson data, and provides a tighter confidence interval than the one based on the count scale while maintaining the nominal 95% coverage
- Poisson or quasi poisson in a regression with count data and . . .
So now, I'm trying a regression with Poisson Errors With a model with all significant variables, I get: Null deviance: 12593 2 on 53 degrees of freedom Residual deviance: 1161 3 on 37 degrees of freedom AIC: 1573 7 Number of Fisher Scoring iterations: 5 Residual deviance is larger than residual degrees of freedom: I have overdispersion
- Poisson paradigm: Why is - Mathematics Stack Exchange
In the independent case, it is basically like the Poisson approximation to the binomial, which you can see by a direct calculation of a limit In the weakly dependent case, you're basically approximating by pretending the dependence isn't there and then applying the previous form
- Standard error; Poisson distribution - Cross Validated
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