similar to: New package: colSums

Mark Leeds <mleeds at mlp.com> wrote (to S-News): > does anyone know the R equivalent of the SPlus rowVars function ? Andy Liaw <andy_liaw at merck.com> replied: > More seriously, I seem to recall David Brahms at one time had created an R > package with these dimensional summary statistics, using C code. (And I > pointed him to the `two-pass' algorithm for variance.)

I need to calculate a large number of t statistics, and would like to do so via matrix operations. So far I have figured out a way to calculate the mean of each row of the matrix: d <- matrix(runif(100000,1,10), 1000, 10) # some test data s <- rep(1,ncol(d)) # a sum vector to use for matrix multiplication means <- (d%*%s)/ncol(d) This is at least 1 order of magnitude faster than

I request that the "freq" argument to hist be deprecated. Reason: One nice thing about SAS is is the consistency of certain inputs across many PROCs. In particular, they have "weight" and "freq" statements. We have added "weights" and "freq" to a number of functions in S-PLUS, listed below. I would like to see the same in R. In porting the

Hi people, If there is a fn "colMeans" why isn't there a "colSDs" etc Thanks, Phil. -- Philip Rhoades Pricom Pty Limited (ACN 003 252 275) GPO Box 3411 Sydney NSW 2001 Australia Mobile: +61:0411-185-652 Fax: +61:2:8923-5363 E-mail: pri at chu.com.au -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi, Currently, the "base" has colSums, colMeans. It seems that it would be useful to extend this to also include colMin, colMax (of course, rowMin and rowMax, as well) in order to facilitate faster computations for large vectors (compared to using apply). Has this been considered before? Please forgive me if this has already been discussed before. Thanks, Ravi Ravi Varadhan, Ph.D.

Hi, all! My project today is to write a speedy colSums(), which is a function available in S-Plus to add the columns of a matrix. Here are 4 ways to do it, with the time it took (elapsed, best of 3 trials) in both R and S-Plus: m <- matrix(1, 400, 40000) x1 <- apply(m, 2, sum) ## R=16.55 S=52.39 x2 <- as.vector(rep(1,nrow(m)) %*% m) ## R= 2.39 S= 8.52 x3 <-

Hi, all, I've been converting code from S-Plus ("S" for short) to R for a few weeks. Here are some differences I've found, aside from the big well-known ones (scoping, models, data storage) and the contents of Kurt Hornik's FAQ section 3.3.3. Let me start with the ones that seem like serious bugs or deficiencies: 1) LETTERS[c(NA,2)] in S is

Also in assign() there some arguments lacking in R such as 'frame' and 'where', though I guess that 'frame' in S may be similar to 'pos' in R. Harvey -----Original Message----- From: David Brahm [SMTP:a215020@agate.fmr.com] Sent: Wednesday, October 03, 2001 11:36 AM To: r-help@stat.math.ethz.ch Cc: Kurt.Hornik@ci.tuwien.ac.at; r-bugs@r-project.org Subject:

Dear R friends I wanted a function to make a simple percent table that would be easy for students to use. The goal originally was to have a simple thing people would call like this pctable(rowvar, colvar, data) and the things "rowvar" and "colvar" might be names of variables in data. I wanted to avoid the usage of "with" (as we now see in the table help). Then

I am using the R 2.2.1 in a Windows XP environment. I have a dataframe with 12 columns and 1,000 rows. (Some of the rows have 1 or fewer values.) I am trying to use rowVars to calculate the variance of each row. I am getting the following message: ?Error in na.remove.default(x) : length of 'dimnames' [1] not equal to array extent? Is there a good work-around?

Hi, I'm using colSums and rowSums to sum the first dimensions of arrays. It works ok but the resulting object is different. See > a3d <- array(rnorm(120, mean=2), dim=c(20,6,1)) > dim(colSums(a3d)) [1] 6 1 > dim(rowSums(a3d)) NULL > class(colSums(a3d)) [1] "matrix" > class(rowSums(a3d)) [1] "numeric" I was expecting rowSums to preserve the array

Hi together, I have some data in a matrix structure - say 1000 rows with 10 columns. And I like to do some calculations (like max, avg or min) on row level. The only solution I found so fare was using a loop like for (i in 1:1000) { max[i] <- max(matrix[I,]) } It looks like that this is not very fast. Does an other way exists? Kind regards Ulrich

As best I understand it, colSums (and associated functions) in S+ 6 are optimized functions (calling special C routines) for doing simple matrix math. For example, it seems like (in S+): all.equal(colSums(m), apply(m, 2, sum)) should be TRUE for any matrix m. It also seems like colSums (and its brethren) are very fast. My question: Are there equivalents to colSums in R? Thanks, Dave Kane

Hi, I have a matrix, say m=matrix(c( 983,679,134, 383,416,84, 2892,2625,570 ),nrow=3 ) i can find its row/col sum by rowSums(m) colSums(m) How do I divide each row/column by its rowSum/colSums and still return in the matrix form? (i.e. the new rowSums/colSums =1) Thanks. Casper -- View this message in context:

For your consideration: > z [,1] [,2] [1,] 1 NA [2,] 2 NA [3,] 3 NA > colSums(z) [1] 6 NA Correct, according to the documentation > colSums(z,na.rm=T) [1] 6 0 Surprising to me, but, as documented, correctly consistent with apply() and >sum(NULL) [1] 0 The documentation for sum() explicitly notes that the sum of an empty set is 0 by definition, so that users

Working with an NxMxO sized matrix, currently I can do this in my code: if (max(colSums(array)) >= number) But to get an equivalent result using rowSums, I have to do: for (i in 1:10) { if (max(rowSums(array[,,i])) >= number) } I'm running both in a much larger loop that loops millions of times, so speed and such is quite a big factor for me. Currently, the colSums line uses about

Hi all, I'm trying to learn R after years of Matlab's experience. Here is an issue I couldn't solve today. Consider the following piece of code (written by memory): for(i in 1:n){ submat <- data[1:i,] C <- colSums(submat) } The problem is that at the first iteration, data[1:1,] reduces to a vector and colSums returns an error. This sounds really strange to me

Full_Name: Doug Grove Version: 1.7.0 OS: Linux Submission from: (NULL) (209.31.211.56) Hi, Minor mistake in the documentation on the colSums page. In the ARGUMENTS section it states for 'dims' that: For `col*', the sum or mean is over dimensions `dims+1, ...'; for `row*' it is over dimensions `1:dims'. These two are reversed. Thanks, Doug Grove

I have a data frame called test shown below that i would like to summarize in a particular way : I want to show the column sums (columns y ,f) grouped by country (column e1). However, I'm looking for the data to be split according to column e2. In other words, two tables of sum by country. One table for "con" and one table for "std" shown in column e2. Finally at the

Hi, I'm using reshape to cast molten data. When I use the following command, R either crashes (when I use Notepad++) or gives an error (when I use Rgui or source()), BUT the error occurs not always, maybe only on half the attempts: w <- cast(v, id + code + productname + year + begin + end + specificDesc + specificDesc2 ~ type) Error in merge.data.frame(data, all.combinations, by =