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- Relationship between poisson and exponential distribution
The waiting times for poisson distribution is an exponential distribution with parameter lambda But I don't understand it Poisson models the number of arrivals per unit of time for example How i
- 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
- Why is Poisson regression used for count data?
I understand that for certain datasets such as voting it performs better Why is Poisson regression used over ordinary linear regression or logistic regression? What is the mathematical motivation
- What advantages does Poisson regression have over linear regression in . . .
Poisson regression would be more suitible in this case because your response is the count of something Putting things simply, we model that the distribution of number of awards for an individual student comes from a poisson distribution, and that each student has their own λ λ poisson parameter The Poisson regression then relates this parameter to the explanatory variables, rather than the
- probability - What is the connection between binomial and poisson . . .
Poisson is also for counting events happening What is the connection between them? I know is that when sample size is large both can be approximated with normal But how are they similar or different? I learned in class their PMF are different but not really understand where does such PMF comes from and intuitive way of explaining them
- r - Rule of thumb for deciding between Poisson and negative binomal . . .
The Poisson distribution implies z ∼ N(0, 1) z ∼ N (0, 1) so a one-sample t t test can provide a P -value for testing Poisson vs negative binomial Another test for equidispersion is the Lagrange Multiplier (∑(μ2 i) − ny¯)2 (2 ∑μ2 i) (∑ (μ i 2) n y) 2 (2 ∑ μ i 2) which follows a one-degree χ2 χ 2 distribution under the null
- Poisson regression to estimate relative risk for binary outcomes
Brief Summary Why is it more common for logistic regression (with odds ratios) to be used in cohort studies with binary outcomes, as opposed to Poisson regression (with relative risks)? Backgrou
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