On Thu, Apr 21, 2011 at 5:34 PM, peter dalgaard <pda...@gmail.com> wrote: > > On Apr 21, 2011, at 16:00 , Bert Gunter wrote: > >> Folks: >> >> It is perhaps worth noting that this is probably a Type III error: right >> answer to the wrong question. The right question would be: what data >> structures and analysis strategy are appropriate in R? As usual, different >> language architectures mean that different paradigms should be used to best >> fit a language's strengths and weaknesses. Direct translations do not >> necessarily do this. > > Hum, there is a point, though: If you take the crude translation approach, > you will soon realize that there is very little that SAS (or SPSS, or...) can > do that you literally can't do in R.
What about reading a deck of punched cards with the cards statement in SAS? How do you propose to do that in R? > It is often the case that there is much neater and well-structured approach > in R, but the flip side is that there are cases where the neat solution is > hard to find, and maybe some cases where it doesn't really exist (e.g. not > everything can be vectorized). This is the sort of thing that in some circles > give R a reputation for being poorly suited for data handling, compared to > the DATA step in SAS. Do notice the circular logic that occurs when defining > "typical statistical task" as "something you can do in SAS", though. > > (One example is "last observation carried forward", a rather dubious > technique for filling in missing observations in longitudinal studies, which > probably directly stems from the RETAIN directive in SAS. > > In R, you may find yourself doing something like > > x[is.na(x)] <- x[!is.na(x)][cumsum(!is.na(x))[is.na(x)]] > > which isn't even completely failsafe. However, you'll get the result soon > enough with > > for (i in seq_len(x)) if (is.na(x[i])) x[i] <- t else t <- x[i] > > and this time, you can actually read the code. > > Of course, approx() will do the trick much more swiftly than either of the > above.) > > -- > Peter Dalgaard > Center for Statistics, Copenhagen Business School > Solbjerg Plads 3, 2000 Frederiksberg, Denmark > Phone: (+45)38153501 > Email: pd....@cbs.dk Priv: pda...@gmail.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. > ______________________________________________ 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.
