Hi Marshall, On Fri, Apr 9, 2010 at 8:59 AM, Marshall Feldman <ma...@uri.edu> wrote: > ... > For any particular set of analyses, one typically recodes variables and > deletes cases and variables. It would be really nice to have a package that, > for example, if one selected cases from a larger data set based on the > values of certain variables would inspect the resulting data and drop any > variables that have the same value for all cases. Similarly, if any cases > are entirely zero or NA, the package could (under user control) drop these > cases. Finally, it could take a set of data transformations and keep them as > an object, so that the same selection/reshape/streamlining can easily be > applied to similar data sets. > ...
Some of the utilities in the caret package might be related to the things your after: http://cran.r-project.org/package=caret There is a writeup about using caret to build predictive models in R in the Journal of Statistical Software (it's a PDF): http://www.jstatsoft.org/v28/i05/paper I'd recommend reading through that if you haven't before, since caret offers many handy wrapper/utility functions, but check out section 3: Data Preparation, in particular, where Max talks about zero-variance-predictors and the multicollinearity problem. Hope that helps. -- Steve Lianoglou Graduate Student: Computational Systems Biology | Memorial Sloan-Kettering Cancer Center | Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact ______________________________________________ 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.
