similar to: trivial typo in ?Matrix::sparse.model.matrix.Rd

Hi, Martin, Ben, et al.: On 2020-07-21 04:33, Martin Maechler wrote: >>>>>> Ben Bolker >>>>>> on Mon, 20 Jul 2020 20:11:04 -0400 writes: >> ? "form" -> "from". Diff against latest SVN: >> Index: sparse.model.matrix.Rd >> =================================================================== >> ---

>>>>> "AS" == Abby Spurdle >>>>> on Wed, 22 Jul 2020 00:28:12 +1200 writes: >> "No documentation for ?sparse.model.matrix? in >> specified packages and libraries", but it's there after >> "library(Ecfun)". I find that interesting, because "Matrix" does not >> appear in the Ecfun

Using the Matrix package, how can I create a row-oriented sparse Matrix from scratch populated with some data? By default a column-oriented one is created and I'm aware of the note that the package is optimized for column-oriented ones, but I'm only interested in using it for holding my sparse row-oriented data and doing basic subsetting by rows (even using drop=FALSE). Here is what I

>>>>> Henrik Bengtsson <henrik.bengtsson at gmail.com> >>>>> on Tue, 19 Apr 2016 14:04:11 -0700 writes: > Using the Matrix package, how can I create a row-oriented sparse > Matrix from scratch populated with some data? By default a > column-oriented one is created and I'm aware of the note that the > package is optimized for

> I would assume that > library(Matrix, include.only="isDiagonal") > implies that only `isDiagonal` ends up on the search path This could also be a reasonable behavior, but neither does that happen today. > I think a far better approach to solve Michael's problem is simply to use > fac2sparse <- Matrix::fac2sparse This does not fully simulate attachment, e.g.

I think we should try to advance and hopefully finalize this thread before we forget about it .. >>>>> Michael Chirico n Thu, 11 Apr 2024 09:10:11 -0700 writes: >> I would assume that >> library(Matrix, include.only="isDiagonal") >> implies that only `isDiagonal` ends up on the search path > This could also be a reasonable

I mistakenly left a write in "/tmp" in the rockchalk package (version 1.8.109) that I uploaded last Friday. Kurt H wrote and asked me to fix today. While uploading a new one, I became aware of a problem I had not seen. The version I uploaded last Friday, 1.8.109, has OK status on all platforms except r-release-windows-ix86+x86_64. I get OK on oldrel-windows and also on devel-windows.

On 2020-07-21 09:00, Martin Maechler wrote: >>>>>> "AS" == Abby Spurdle >>>>>> on Wed, 22 Jul 2020 00:28:12 +1200 writes: > >> "No documentation for ?sparse.model.matrix? in > >> specified packages and libraries", but it's there after > >> "library(Ecfun)". I find that interesting,

Hi, we have installed R-2.8.1 using the current pgi compiler (8.0.2) for AMD64 on a SLES9 system. When I try to install "Matrix" everything is fine until the last step. make[1]: Leaving directory `/tmp/R.INSTALL.TW3399/Matrix/src/AMD' pgCC -L/usr/lib64 -L/usr/X11R6/lib64 -pgf90libs -o Matrix.so CHMfactor.o Csparse.o TMatrix_as.o Tsparse.o init.o Mutils.o chm_common.o

64-bit R-2.12.0 was installed on Sun SPARC Solaris 10. Compiler used is solstudio12.2. Attached is the configure script. I then tried to install a recommended package called Matrix. The compilation failed with the following messages, ....... CC -library=stlport4 -G -L/opt/csw/lib/sparcv9 -L/opt/solstudio12.2/prod/lib/v9 -o Matrix.so CHMfactor.o Csparse.o TMatrix_as.o Tsparse.o init.o Mutils.o

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi, I'm doing some basic operations on large sparse matrices, for example getting a row. it takes close to 30 seconds on a 3Ghz machine, and shots the memory usage up to the sky. I suspect there are dense intermediary steps (which, if true would defeat the purpose of trying to use sparse representaitons). As much as I try understanding the

Dear Developers, motivated by the new Sun Studio checks I compiled R-devel and several of our packages with Sun Studio 12 on Fedora x64. Everything worked fine and R-devel runs, with the exception of package Matrix where compilation crashes with the following message. The error occurs during building of the recommended packages and also if Matrix is compiled separately: [...] CC -G -lCstd

Hello, I am working with a sparse matrix that is approx. 13,900 by 14,100. My goal is to select a row out of the matrix and create a new matrix with that row repeated 13,900 times without having to do any looping. Example: Starting Matrix: exampleMatrix 3 x 4 sparse Matrix of class "dgCMatrix" [1,] 1 . . . [2,] . 1 . 0.5 [3,] . . 1 .. New Matrix:.. newExampleMatrix 3 x 4 sparse

Dear all R-users, When I install the package "lme4" in R-2.11.1, and use it to run the simulation on the Linux system, it appears the following problem. Attaching package: 'lme4' The following object(s) are masked from 'package:stats':     AIC Error in names(argNew)[1] <- names(formals(new))[[1]] :   replacement has length zero Calls: initial ... lmerFactorList

> By the way, Ecfun includes some 32 "suggests" and "imports". > "Matrix" is not one of them, but it must be called by something else > that's loaded by Ecfun, to get the result I got. Spencer, I find some of your comments/questions on R packages, extremely basic. (Sorry, if that sounds condescending, but I'm wondering if your comments/questions

Hi all, I have trouble to compile Matrix packages on Solar10 x86-64 with Sun compilers. I saw some postings on this but am not sure how to solve this problem. It is becoming critical as I cannot install biocLite() because of its dependency on Matrix. Could you direct me how to resolve the issue? Thanks in advance! Dongseok R version 2.8.1 (2008-12-22) Copyright (C) 2008 The R Foundation for

Right now, attaching the same package with different include.only= has no effect: library(Matrix, include.only="fac2sparse") library(Matrix) ls("package:Matrix") # [1] "fac2sparse" ?library does not cover this case -- what is covered is the _loading_ behavior of repeated calls: > [library and require] check and update the list of currently attached packages and

Hi, I wish to compute multivariate test statistics for a within-subjects repeated measures design with anova.mlm. This works great if I only have two factors, but I don't know how to compute interactions with more than two factors. I suspect, I have to create a new "grouping" factor and then test with this factor to get these interactions (as it is hinted in R News 2007/2), but

hello list, i'd very much appreciate help with setting up the contrast for a 2-factorial crossed design. here is a toy example: library(multcomp) dat<-data.frame(fac1=gl(4,8,labels=LETTERS[1:4]), fac2=rep(c("I","II"),16),y=rnorm(32,1,1)) mod<-lm(y~fac1*fac2,data=dat) ## the contrasts i'm interressted in: c1<-rbind("fac2-effect in

Let's say I have a within-subject experiment with 2 observables, obs1 and ob2 and 2 independent factors, fac1 and fac2. I can do summary( aov( obs1~fac1*fac2 + Error(Subject/(fac1*fac2)) ) ) summary( aov( obs2~fac1*fac2 + Error(Subject/(fac1*fac2)) ) ) to test the 2 observables separately. > summary( fit<-manova( cbind(obs1,obs2)~fac1*fac2 + Error(Subject/(fac1*fac2)) ) ) gives