Specifying nk=0 to force all effects to be linear will speed things up. Frank
aajit75 wrote > > Hi List, > > Working on the large data frame (number of records=35000 and number of > variables=160). > Using redun() for dropping variables before using into model. > > V <- redun(~., data = data.frame, r2 = 0.8) > > It takes enormously high time for execution, is there anything wrong in > the script? > Suggest any other similar function available for dropping redundant > variables. > > Thanks in advance! > ~A > ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Similar-function-for-Redun-from-Hmisc-tp4095455p4095771.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
