The 'findCorrelation' function in the caret package may be helpful.
On Tue, Apr 19, 2011 at 3:10 PM, Rita Carreira <ritacarre...@hotmail.com> wrote: > > Hello R Users! > I have a data frame that has many variables, some with missing observations, > and some that are correlated with each other. I would like to subset the data > by dropping one of the variables that is correlated with another variable > that I will keep int he data frame. Alternatively, I could also drop both the > variables that are correlated with each other. Worry not! I am not deleting > data, I am just finding a subset of the data that I can use to impute some > missing observations. > I have tried the following statement > dfQuc <- dfQ[ , sapply(dfQ, function(x) cor(dfQ, use = > "pairwise.complete.obs", method ="pearson")<0.8)] > but it gives me the following error: > Error in `[.data.frame`(dfQ, , sapply(dfQ, function(x) cor(dfQ, use = > "pairwise.complete.obs", : > undefined columns selected > Since I have several dozen data frames, it is impractical for me to manually > inspect the correlation matrices and select which variables to drop, so I am > trying to have R make the selection for me. Does any one have any idea on how > to accomplish this? > Thank you very much! > Rita ===================================== "If you think education is > expensive, try ignorance."--Derek Bok > > > > [[alternative HTML version deleted]] > > ______________________________________________ > 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.
