(This article was first published on Getting Genetics Done, and kindly contributed to R-bloggers)
It took me a while to figure this out, so I thought I'd share. I have a dataframe with millions of observations in it, and I want to estimate a density distribution, which is a memory intensive process. Running my kde2d function on the full dataframe throws and error -- R tries to allocate a vector that is gigabytes in size. A reasonable alternative is to run the function on a smaller subset
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Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).