Hello! i know these are basic but i cannot seem to find the answer thru my searches..
1) Can someone recommend an equivalent to SAS PROC Standardize in R? I am in need to frequently standardize a data frame, with z-scores, or squash to 0-1 scale - is there a slick function or package someone can recommend? 2) Also, have data sets with a lot of predictor variables. in the diabetes data frame i see that fields have been grouped to X and Y variables, making it very easy to identify X and Y in the regression techniques. How is this done, how do you group lets say a group of columns into 1 matrix, within a data frame. example: the AsIs group is a matrix of X variables: > str(diabetes) `data.frame': 442 obs. of 3 variables: $ x : AsIs [1:442, 1:10] 0.038075.... -0.00188.... 0.085298.... -0.08906.... 0.005383.... ... ..- attr(*, "dimnames")=List of 2 .. ..$ : NULL .. ..$ : chr "age" "sex" "bmi" "map" ... ..- attr(*, "class")= chr "AsIs" $ y : num 151 75 141 206 135 97 138 63 110 310 ... $ x2: AsIs [1:442, 1:64] 0.038075.... -0.00188.... 0.085298.... -0.08906.... 0.005383.... ... ..- attr(*, ".Names")= chr "age" "age" "age" "age" ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr "1" "2" "3" "4" ... .. ..$ : chr "age" "sex" "bmi" "map" ... ..- attr(*, "class")= chr "AsIs" ______________________________________________ [email protected] 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.
