Sounds like a finite mixture model. I haven't read your references but an overall model for such an approach could be
f(Y=0; pi, kappa) = 1- pi + pi*f(Y=0|Z=1; kappa) where pi=Pr(Z=1) is the probability of an event, z, and y is the value observed when the event occurs and f is the probability density of Y with parameters kappa. You could try 'fmr' in Jim Lindsey's gnlm package (available at http://www.commanster.eu/rcode.html ) which fits generalized nonlinear regression models with two or three point mixtures using maximum likelihood. > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- > project.org] On Behalf Of Kirsten Martin > Sent: Wednesday, November 28, 2012 1:33 PM > To: r-help@r-project.org > Subject: [R] Conditional model in R > > Hello all, > > I have a data set where the response variable is the percent cover of a > specific plant (represented in cover classes 0,1,2,3,4,5, or 6). This > data > set has a lot of zeros (plots where the plant was not present). > I am trying to model cover class of the plant as a function of both > total > nitrogen and shrub cover. > > After quite a bit of research I have come across a conditional approach > to > modeling data with a lot of zeros (Fletcher et al. 2005, Welsh et al. > 1996). > In this approach you model the presence/absence data using a logistic > regression and then model the presence only data using ordinary (least > squares) regression. > > I have successfully come up with both a logistic model and an ols model > with > good fits. I am running into trouble combining the two (as outlined in > the > third step of the Fletcher et al. 2005 paper). > > Does anyone have any experience or any advice on doing this? How does > one > come up with an overall model for the data using this approach? > > Thanks for your help! > Kirsten > > > > -- > View this message in context: > http://r.789695.n4.nabble.com/Conditional-model-in-R-tp4651188.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@r-project.org mailing list > 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. ______________________________________________ R-help@r-project.org mailing list 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.
