Ok, I have searched and searched and just have no clue where to start. First, what I would like to do is produce a QQ-plot (or even a readable residual plot) to look at the fit of my model. I guess I just don't understand how the parameters that go into
qnbinom() are obtained from the output of
MASS::glm.nb(). I am attempting to use
probplot() from package e1071, but am unsure of the inputs needed. It would be great if someone having experience with fitting negative binomials could lend a hand.
Secondly, I came across a residual plot here: http://www.stat.cmu.edu/~hseltman/Rclass/R8.R I can make it to work, but I don't know how to interpret it or if I am using it correctly. Has anyone else used this?
At the moment I am relying on the AIC and plots of fitted vs. actual values to assess the fit of my model and I would like something a little better!
Hopefully this will clarify what I am asking. With
qnbinom(p, size, prob, mu, lower.tail = TRUE, log.p = FALSE), how do I (or is it even possible to) get the
mu from the output of a
glm.nb fit model? From my research, I have found that size is the dispersion parameter, but other than that I'm not sure where to go. I know theta goes in there somehow, just not sure how to get it in the form needed.
Edit 2: Ok, once I have a
distplot(), is there a guide to interpreting it? I am fairly positive I have a bad fit because I have a curved plot with a red line going through it (with many points on the tails far from the red line). The prob: ML = 0.011, is this rejecting that the distribution is from the negative binomial specified?