> On Oct 2, 2017, at 2:05 AM, David <dasol...@hotmail.com> wrote: > > Dear list, > > > I am just starting on analysis of count data in R 3.4.0. My dataset was > obtained from counting particles on a surface before andd after a cleaning > process. The sampling positions on the surface are pre-defined and are the > same before and after cleaning. I have ~20% of 0's. I want to know if the > cleaning process was useful at reducing the number of particles. > > > I first fit a negative binomial model using > > >> nbFit<-glmer.nb(Count ~ Cleaning + (1|Sampling_point) , data = myCountDB) > > > > I now would like to add a curve to the histogram representing the negative > binomial density function fitted to my data using > > >> curve(dnbinom(x=, size=, prob=, mu=), add=TRUE)
Why not use the predict function in that package? See ?merMod -- David. > > > But I am struggling defining the arguments to dnbinom. > > > Using the str() function on the nbFit object I see there are many fields > returned. And I get lost reading the ?glmer.nb help, greatly because of my > lack of knowledge. Which ones should I use? > > > Thanks ever so much for your valuable help > > > Dave > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. David Winsemius Alameda, CA, USA 'Any technology distinguishable from magic is insufficiently advanced.' -Gehm's Corollary to Clarke's Third Law ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
