similar to: %*% in examples (PR#855)

I don't use SPSS but following through on your detective work can provide the likely answer. First note that both date numbers are evenly divisible by the number of seconds in a day, i.e. 24*60*60. This suggests that these numbers are seconds since some origin. Since we know "2003/02/11" corresponds to 13264300800 we deduce that the origin must be spss.orig <-

Hi, is anybody out there who knows APL and would help me to translate 52 lines of APL code into propper R? best, Torsten

Hi, the following example aiming at a class containing a logical slot segfaults under R-1.9.0 when `gctorture(on = TRUE)' is used: Code code (dummy.c): #include <Rdefines.h> SEXP foo() { SEXP ans; PROTECT(ans = NEW_OBJECT(MAKE_CLASS("test"))); SET_SLOT(ans, install("lgl"), allocVector(LGLSXP, 1)); LOGICAL(GET_SLOT(ans,

r-devel from this morning says hothorn@www:~ > R R : Copyright 2001, The R Development Core Team Version 1.4.0 Under development (unstable) (2001-12-09) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type icense()' or icence()' for distribution details. R is a collaborative project with many contributors. Type

I suppose that multcomp in R and multicomp in S-Plus are related and it appears that it is possible to use multicomp with lme in S-Plus given the following correspondence on s-news sally.rodriguez at philips.com 12:57 p.m. 24/04/03 -0400 7 [S] LME summary and multicomp.default() Is it possible to use multicomp with lme in R and if so what is the syntax from a simple readily available

Hi, the graphical parameter "cex.axis" does not have any affect for "boxplot": data(iris) boxplot(iris[,1:4], ylab="y", cex.lab=2, cex.axis=2) The patch is simply adding "cex.axis" to the search for axis relevant parameters in "bxp": ax.pars <- pars[names(pars) %in% c("xaxt", "yaxt", "las",

To the plot experts: when creating a plot containing different lines, each with a special line type, it may happen that the result of 'postscript()' is not readable by ghostview (which may not be an R error, thus not bug report ;-). This is the case when mixing lty as 0:6 and character or even when using lty as character only. Example: postscript("test.ps") plot(1:10,

Hello, I use t.test for normal distributed and wilcox.test for non-normal distributed samples. It is easy to write a function for t.test that calculates the effect size, because all parts of the formula are available from the t.test result: r = sqrt(t*t / (t*t + df)) However, for Wilcoxon tests, the formula for effect sizes is: r = Z / sqrt(N) I wonder how I can calculate the Z-score in R for

The `examples' section says plot.mlm # to see how the "NotYetImplemented" # reference is made automagically ^ Best, Torsten

Hi, currently the "label" and "edgetext" attributes of a dendrogram are coerced to character before they are added to a plot with `text'. Is there a specific reason to do so (expect for the determination of the size of the character string to be plotted)? Otherwise one could plot the attributes directly via diff dendrogram.R /usr/src/R/src/library/stats/R/dendrogram.R

Dear developeRs, I thought that backslashes can be escaped in the usual way (and I think I did this before) but I can't see why R> gsub("\\", "x", "\alpha") Error in gsub(pattern, replacement, x, ignore.case, extended, fixed, useBytes) : invalid regular expression '\' gives an error. Or am I just blind? Best, Torsten R> version

Hi, a friend of mine came across this R> x <- 1:5 R> cbind(x,x) x x [1,] 1 1 [2,] 2 2 [3,] 3 3 [4,] 4 4 [5,] 5 5 R> rbind(x,x) [,1] [,2] [,3] [,4] [,5] x 1 2 3 4 5 x 1 2 3 4 5 x is a vector and therefore has no dim-attribute. Obviously cbind treats x as a col-vector but rbind treats x as a row-vector, that is: two functions have a different

Hi, in last nights alpha version, `var' is broken: R> var(rnorm(100)) Error in var(rnorm(100)) : 3 arguments passed to "cov" which requires 4. which I suspect is due to recent changes to `cov'. The same is true for R> cov(rnorm(100), rnorm(100)) Error in cov(rnorm(100), rnorm(100)) : 3 arguments passed to "cov" which requires 4. Best, Torsten R> version

torsten@www:/raid/home/torsten > ping rsync.r-project.org PING franz.stat.wisc.edu (128.105.174.95): 56 data bytes --- franz.stat.wisc.edu ping statistics --- 12 packets transmitted, 0 packets received, 100% packet loss Torsten -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

Hi, did anybody manage to compile F90 sources in an R-package? The major problem is, at least in my opinion, that non of the "free" F90 -> F77 converters is working correctly, at least for the F90 sources I need to compile. Torsten -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read

Hello R-users, I would like to generate two-way contingency tables with zero in one cell. I tried to use the function r2dtable but I could not force one cell to have zero value. Any Idea? Best regards.. Mahmoud [[alternative HTML version deleted]]

the NEWS file in 1.4.0-devel states: o mean() has `data frame' method applying mean column-by-column. When applied to non-numeric data mean() now returns NA rather than a confusing error message (for compatibility with S4). which means: R> mean(c(TRUE, FALSE)) [1] NA Warning message: argument is not numeric: returning NA in: mean.default(c(TRUE, FALSE)) but: R>

Dear All, I am using wilcox.test to test two samples, data_a and data_b, earch sample has 3 replicates, suppose data_a and data_b are 20*3 matrix. Then I used the following to test the null hypothesis (they are from same distribution.): wilcox.test(x=data_a, y=data_b, alternative="g") I got pvalue = 1.90806170863311e-09. When I switched data_a and data_b by doing the following:

Hello, why does > test <- rank(sample(10)) > test [1] 4 8 9 10 2 1 7 6 3 5 > is.integer(test) [1] FALSE > is.double(test) [1] TRUE make sense in R-1.1.1? Torsten -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or

Hi, this is maybe not a real R problem but I want to solve this in R ;-) Consider the set of all permutations of 1:N (=: S, say) and a fixed element a from S. I now need to compute the number of permutations s from S which are elementwise less or equal to a: | { s \in S | s <= a } | Of cource, backtracking using a tree structure is possible. Does anyone know an efficient way? Torsten