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I'm looking for a formula for memory usage in standard regression; that is, if I have X rows with Y predictors, how much memory is needed? I'm speccing out a system, and I'd like to be able to get enough memory that we can do some fairly large regressions. ==Ed Freeman [[alternative HTML version deleted]]

Hi all, Just thought I'd post this (maybe) helpful tool I wrote. For people like me who are bad at keeping a clean environment, it's a time-saver. #simple command to get only one type of object in current environment lstype<-function(type='closure'){ inlist<-ls(.GlobalEnv) if (type=='function') type <-'closure'