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
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
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] - \\
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 Poisson regression is frequently taught as a method for analyzing counts It is somewhat under emphasized that such a probability model works exceptionally well for modeling 0 1 outcomes, especially when they are rare
How to calculate a confidence level for a Poisson distribution? 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) = 47 18182 what would the 95% confidence look like for this?
arrival time poisson processes - Cross Validated The arrival times of customers in a bakery can be modeled by a Poisson process (Nt)t≥0 with some rate λ > 0 On average, there are four arrivals per unit of time I want to ask about the question