[R-sig-ME] question on nbinom1

[Don Cohen]

Thank you.
This is perfectly clear and enables further analysis.
I hope you can arrange to put it in some (even better, much) documentation.
I wish it were in wikipedia.

Ben Bolker writes:
 > 
 >    I believe the R d/p/q/r functions corresponding to glmmTMB's 
 > implementation of *nbinom1 would look like this:
 > 
 > 
 > rnbinom1 <- function(n, mu, phi) {
 >      ## var = mu*(1+phi) = mu*(1+mu/k) -> k = mu/phi
 >      rnbinom(n, mu=mu, size=mu/phi)
 > }
 > 
 > dnbinom1 <- function(x, mu, phi, ...) {
 >      dnbinom(n, mu=mu, size=mu/phi, ...)
 > }
 > 
 > pnbinom1 <- function(q, mu, phi, ...) {
 >      pnbinom(q, mu=mu, size=mu/phi, ...)
 > }
 > 
 > qnbinom1 <- function(p, mu, phi, log=FALSE) {
 >      pnbinom(p, mu=mu, size=mu/phi, ...)
 > }
 > 
 > 
 >    (there would be an even more clever/inscrutable way to do this by 
 > transforming the body of the code, without repeating oneself so much, 
 > but it would probably be a bad idea)
 > 
 > On 10/12/20 6:34 AM, Mollie Brooks wrote:
 > > I think the easiest way to get a numerical representation of the distribution from a fitted model would be using the simulate function.
 > > 
 > > There's an example of how to do that on pages 392-393 of this pdf (including Figs 6 and 7)
 > > https://journal.r-project.org/archive/2017/RJ-2017-066/RJ-2017-066.pdf <https://journal.r-project.org/archive/2017/RJ-2017-066/RJ-2017-066.pdf>
 > > 
 > > cheers,
 > > Mollie
 > > 
 > >> On 10Oct 2020, at 14:23, Don Cohen <don-lme4 using isis.cs3-inc.com> wrote:
 > >>
 > >> Mollie Brooks writes:
 > >>
 > >>> I don't have a copy of Hardin & Hilbe 2007 on hand, but I answered
 > >>> a few of your questions below.
 > >>
 > >> Thank you.
 > >>
 > >> One more question:
 > >>
 > >> How can I compute the nbinom1 distribution?
 > >> Is there a formula for the pdf or cdf ?  An R function ?
 > >>
 > > 
 > > 
 > > 	[[alternative HTML version deleted]]
 > > 
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 > >
 > 
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