Continuous distribution for zero or positive values (in GLM or GLMM)
You could use the bbmle package http://cran.r-project.org/web/packages/bbmle/index.html It allows you to use any distribution and very complex models; however, you can't use random effects. It does require you to program in the distributions, and you will have to use likelihood tests to get a p-value. But I have had high success with fitting zero-inflated data with this package. Kyle
On May 18, 2011, at 11:46 AM, Fred Takahashi wrote:
Hello, just a basic question: what distribution I should use to analyze continuous data which can had zero or positive values (eg. mass of grasses in plots assuming that zero mass is meaningful)? My expected analysis is in the framework of GLM or GLMM (or alternatively, GAM / GAMM). One idea I had is to add 0.0001 to all values and use family=Gamma. That is a good approach? If a better choice is to use a different distribution, suggestions of packages to do that are welcome. Thanks, Fred Takahashi Universidade de Bras?lia - Brasil
_______________________________________________ R-sig-ecology mailing list R-sig-ecology at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Kyle Hernandez Ph.D. Candidate Purdue University Department of Biological Sciences Lilly B-203 765-494-5894 kmhernan at purdue.edu