[R] Trouble building R2.1.0 from source on Linux: package VR

Hi, Following on from suggestions made last week, I decided to install R 2.1.0 on my Linux machine. I'm running into a problem there however, as shown: make[1]: Entering directory `/d0/home/fgibbons/tmp/R2.1.0/R-2.1.0/src/library/Recommended' make[2]: Entering directory

Re: [R] possible bug in merge with duplicate blank names in 'by' field.

Thanks for your quick responses, Gabor and Brian. I'm currently running R version 1.9.1 on Linux. Actually, I have just tested this on R v.2.1.0 running under Windows XP, and indeed, as you both indicate, the problem does not exist on that version for that OS. So, at an appropriate time I'll

[R] possible bug in merge with duplicate blank names in 'by' field.

Run this: p - c('a', 'c', '', ''); a - c(10, 20, 30, 40); d1 - data.frame(Promoter=p, ip=a) # Note duplicate empty names in p. p - c('b', 'c', 'd', ''); a - c(15, 20, 30, 40); d2 - data.frame(Promoter=p, ip=a) all - merge(x=d1, y=d2, by=Promoter, all=T) all - merge(x=all, y=d2, by=Promoter,

Re: [R] lda source code

. -Frank Gibbons At 05:47 PM 10/1/2003, you wrote: Wei Geng wrote: I am new to R. Trying to find out how lda() {in MASS R1.8.0 Windows} was implemented in R. Does anyone know where to find out lda source code ? Thanks. Here: http://cran.r-project.org Hint: MASS is a *package*. You want to view its

[R] Cook-distance-type plot (vertical bars)

, aov.R), and couldn't find anything. Maybe I overlooked it? Thanks -Frank Gibbons PhD, Computational Biologist, Harvard Medical School BCMP/SGM-322, 250 Longwood Ave, Boston MA 02115, USA. Tel: 617-432-3555 Fax: 617-432-3557 http://llama.med.harvard.edu/~fgibbons

Re: [R] Cook-distance-type plot (vertical bars)

Thanks to all who responded, and so promptly too: it works exactly as you describe. Figure 13 of Emmanuel Paradis's R for Beginners was produced by termplot working on an aov object. No, it was produced by plot() working on a aov object, as its caption indicates. The termplot() is Figure 14.

Re: [R] discriminant function

Stefan, I asked the same question last week. As Brian Ripley, its author, said then (and others), the only way to see what's going on is to read the code. It's pretty complicated statistically (that's why the performance is so good!), many of the details are in chapter 2 of Pattern Recognition

[R] LDA in R: how to extract full equation, especially constant term

, -Frank Gibbons PhD, Computational Biologist, Harvard Medical School BCMP/SGM-322, 250 Longwood Ave, Boston MA 02115, USA. Tel: 617-432-3555 Fax: 617-432-3557 http://llama.med.harvard.edu/~fgibbons __ [EMAIL PROTECTED] mailing list https