Nothing
# syn.nb2.r Synthetic NB2
# Table 9.3: Hilbe, Negative Binomial Regression, 2 ed, Cambridge Univ Press
library(MASS)
nobs <- 50000
x1 <- qnorm(runif(nobs)) # random normal N[0,1] variate
x2 <- qnorm(runif(nobs)) # random normal N[0,1] variate
xb <- 2 + .75*x1 - 1.25*x2 # parameter values
a <- .5 # assign value to ancillary parameter
ia <- 1/.5 # invert alpha
exb <- exp(xb) # Poisson predicted value
xg <- rgamma(n = nobs, shaep = a, rate = a) # generate gamma variates given alpha
xbg <-exb*xg # mix Poisson and gamma variates
nby <- rpois(nobs, xbg) # generate NB2 variates
jhnb2 <-glm.nb(nby ~ x1 + x2) # model NB2
summary(jhnb2)
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.