Dear All I am trying to fit a multinomial logistic regression to a data set with a size of 94279 by 14 entries. The data frame has one "sample" column which is the categorical variable, and the number of different categories is 9. The size of the data set (as a csv file) is less than 10 MB.
I tried to fit a multinomial logistic regression, either using vglm() from the VGAM package or mlogit() from the mlogit package. In both cases the estimation crashes because I do not have enough memory, although the free memory before starting the regression is more than 2GB. The regression functions eat up all of my memory. Does anyone know why this relatively small data set leads to memory problems, and how I could work around my problem? thank you for your help, Daniel ______________________________________________ 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.
