similar to: Suggestion: Adding quick rowMin and rowMax functions to base package

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. On Sun, Feb 13, 2011 at 10:18 AM, TakeoKatsuki <takeo.katsuki at gmail.com> wrote: > > Hi Henrik, > > It would be nice if functions of the matrixStats package can handle array > data. > For example, rowSums() of the base package sums along the third axis of an > array by rowSums(x, dim=2). That is a good idea. This was indeed the initial objective before starting

I can repeatably crash R (segfault) by doing n <- 10 z <- data.frame(a=1:n,b=1:n) View(z) and then hitting the "End" key on my keyboard. I haven't got debugging going yet, but running under gdb (without debugging symbols) does give this: 0xb7b63583 in strlen () from /lib/tls/i686/cmov/libc.so.6 R version 2.6.2 (2008-02-08) i486-pc-linux-gnu [Ubuntu Gutsy] locale:

I really want to do this: abline( a=tan(-kT*pi/180), b=kY-tan(-kT*pi/180)*kX ) where kX,kY and kT are vectors of equal length. But I can't do that with abline unless I use a loop, and I haven't figured out the least unelegant way of writing the loop yet. So is there a way to do this without a loop? Or if I am to resort to the loop, what's the best way of doing it considering that I

Dear expeRts, I have two matrices A and B. They have the same number of columns but possibly different number of rows. I would like to compare each row of A with each row of B and check whether all entries in a row of A are less than or equal to all entries in a row of B. Here is a minimal working example: A <- rbind(matrix(1:4, ncol=2, byrow=TRUE), c(6, 2)) # (3, 2) matrix B <-

Thanks for the response. I looked and I cannot see what exactly I need. I saw getCalledFunction() so I need CallSite CS(cast<Value>(II)) where II is a basic block iterator, so an instruction. It seems not easier than the "unelegant" version....if I am still at the Instruction level... I need a method that takes from a "leaf" basic block from a function (Maybe there is

I have following files. list.rhtml ----------------------- <ul id="items"> <%= render(:partial => ''item'', :collection => @items) %> </ul> _item.rhtml ------------------------ <li id="<%= item.id %>" > <%= item.name %> <%= item.body %> </li> edit.rjs ------------------------ page.replace_html

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

Hi, On 26/04/13 13:17, Alexandru Ionut Diaconescu wrote: > Thanks for the response. > I looked and I cannot see what exactly I need. I saw getCalledFunction() so I > need CallSite CS(cast<Value>(II)) where II is a basic block iterator, so an > instruction. It seems not easier than the "unelegant" version....if I am still > at the Instruction level... the call graph

Aloha, I just made some quick hacks on the configure script with the 'ncdf' package to make it link with the opendap/dods libraries (opendap.org) rather than the netcdf api library. Basically, this allows a user to interact in R with a remotely served dataset as if it were a netcdf file on the local filesystem (read-only). Functionality with local files should continue to work as

On Tue, Feb 20, 2018 at 11:58 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > Ista, et. al: efficiency? > (Note: I needed to correct my previous post: do.call() is required for > pmax() over the data frame) > > > x <- data.frame(matrix(runif(12e6), ncol=12)) > > > system.time(r1 <- do.call(pmax,x)) > user system elapsed > 0.049 0.000

It looks like OP uses a data.frame, so in order to use matrixStats (I'm the author) one would have to pay the price to coerce to a matrix before using matrixStats::rowMaxs(). However, if it is that the original data could equally well live in a matrix, then matrixStats should be computational efficient for this task. (I've seen cases where an original matrix was turned into a data.frame

Hi, thank you for taking the time and reading my question. My question is twofold: 1. I have several matrices with variables and one matrix with water levels. I want to predict the water level with the data in the other matrices. Basically, * mod<-lm(matrix1 ~ matrix2+matrix3)* ( What looks like a minus is meant to be the wiggly minus.) Of course I could dissemble the matrices and paste

Hello all, I have a question which I have been struggling with for several weeks now, that I think might be easy for more proficient coders than myself. I have a large behavioral dataset, with behaviors and the times (milliseconds) that they occurred. Each subject has a separate file, and a sample subject file can be generated using the following syntax: Time <- c(1000, 1050, 1100, 1500, 2500,

Here's a patch that should make predict.glm(..., type="response") retain the names. The change passes make check on our Opteron running SLES9. One simple test is: names(predict(glm(y ~ x, family=binomial, data=data.frame(y=c(1, 0, 1, 0), x=c(1, 1, 0, 0))), newdata=data.frame(x=c(0, 0.5, 1)), type="response")) which gives [1]

Hello, Within the development of a package, I would need to build a specific method for the "pmin" function. I first make "pmin" generic pmin <- function (..., na.rm = FALSE) UseMethod("pmin") pmin.default <- base::pmin Now, within my new method, I would like to change the arguments in . (dot dot dot) before sending it to the NextMethod.

A new release 0.13.1 of matrixStats is now on CRAN [http://cran.r-project.org/package=matrixStats]. The source code is available on GitHub [https://github.com/HenrikBengtsson/matrixStats]. WHAT DOES IT DO? The matrixStats package provides highly optimized functions for computing common summaries over rows and columns of matrices, e.g.rowQuantiles(). There are also functions that operate on

A new release 0.13.1 of matrixStats is now on CRAN [http://cran.r-project.org/package=matrixStats]. The source code is available on GitHub [https://github.com/HenrikBengtsson/matrixStats]. WHAT DOES IT DO? The matrixStats package provides highly optimized functions for computing common summaries over rows and columns of matrices, e.g.rowQuantiles(). There are also functions that operate on

Hi, I have two questions want to ask. 1. If I have a matrix like this, and I want to figure out the rows whose value in the 3rd column are less than 0.05. How can I do it with R. hsa-let-7a--MBTD1 0.528239197 2.41E-05 hsa-let-7a--APOBEC1 0.507869409 5.51E-05 hsa-let-7a--PAPOLA 0.470451884 0.000221774 hsa-let-7a--NF2 0.469280186 0.000231065 hsa-let-7a--SLC17A5

A few hours ago, I was making a small point on the R-SIG-robust mailing list on the point that ifelse() was not too efficient in a situation where pmax() could easily be used instead. However, this has reminded me of some timing experiments that I did 13 years ago with S-plus -- where I found that pmin() / pmax() were really relatively slow for the most common case where they are used with only