Quantile-Quantile Plot for Negative Binomial Distribution I am performing regression analysis in R on count data which are negative binomial distributed. I would like to use a quantile-quantile plot as a tool to diagnose the fit of my models, but I am struggling to find an appropriate method for my data. A Normal Q-Q plot would not be appropriate since the residuals are not expected to be Normally distributed, so I think I need to compare my residuals against theoretical quantiles from the negative binomial distribution. I have tried using the 'qqPlot' function from the 'car' package, but I can't seem to get it to work properly.

Normally distributed residuals can be generated using the randomized quantile residual method. For example
library(MASS)
fit <- glm(Days ~ .^4, family = negative.binomial(2), data = quine)
library(statmod)
res <- qresid(fit)
qqnorm(res)
qqline(res)

Here the MASS package provides the negative.binomial GLM family and the quine data example, while the qresid function is part of the statmod package.
