similar to: finding big matrix size and SVD

Greeting R helpers J I am not familiar with R but I have to use it to analyze data set that I have (30,000 20,000) I want to change the structure of the dataset and I am wondering how that might be possible in R A main data looks like this: some entities are empty Age No. Age No. Age No. Center1 5 2 8 7

Hi, I run a maanova analysis and found this message error: Error in ma.svd(X, 0, 0) : 0 extent dimensions I did a google search and found this: \item ma.svd: function to compute the sigular-value decomposition of a rectangular matrix by using LAPACK routines DEGSVD AND ZGESVD. \item fdr: function to calculate the adjusted P values for FDR control. I did a search for LAPACK and

Dear All, I need to perform a SVD on a very large data matrix, of dimension ~ 500,000 x 1,000 , and I am looking for an efficient algorithm that can perform an approximate (partial) SVD to extract on the order of the top 50 right and left singular vectors. Would be very grateful for any advice on what R-packages are available to perform such a task, what the RAM requirement is, and indeed what

Dear Sir or Madam, I am very new to R, and I am trying to install seqinr-package. In the manual I read that I need to install ape-package first, and I failed to do it. I had the following error messges: /usr/bin/ld: cannot find -lgfortran collect2: ld returned 1 exit status make: *** [ape.so] ?????? 1 ERROR: compilation failed for package 'ape' ** Removing

Dear R community, I have a data matrix (531X314), and would like to apply the prcomp. However, I got this error Lapack message. I am using R3.2.2. I googled a bit and found that it might be related to converge issue. ?Just wonder if there is a way to get around it? Thank you very much! Ace On Thursday, December 29, 2016 11:44 AM, Ista Zahn <istazahn at gmail.com> wrote: Use

Hi Ian, Natasha and I are interested in helping with the io emulation work for fully virtualized HVM guests you mentioned in your March 12th email: http://lists.xensource.com/archives/html/xen-devel/2006-03/msg00394.html In the post, you mentioned the following tasks: - get minios running on x86_64 - port xenbus/netfront/blkfront to minios - compile qemu-dm into minios - redirect IO to qemu-dm

Hi Duncan, Thanks for your reply. Yes, it does seem to be specific to the CTYPE setting to Chinese on Windows. If I set it to English using Sys.setlocale() there is no problem, then back to Chinese and the authors disappear: Sys.setlocale("LC_ALL","English") citation("readr") #' To cite package ?readr? in publications use: #' #' Hadley Wickham, Jim

Hi, Duncan i have forwarded this thread to Nathan, who promised to look into it. Andrie On 17 Jun 2017 17:26, "Duncan Murdoch" <murdoch.duncan at gmail.com> wrote: > On 17/06/2017 9:13 AM, Ben Marwick wrote: > >> Hi Duncan, >> >> Thanks for your reply. Yes, it does seem to be specific to the CTYPE >> setting to Chinese on Windows. If I set it to

Hi to all, Here is a question which I cannot solve. Appreciate so much for any suggestions! I have a squared region which is irregularly divided into many rectangular patches. Each patch is associated with a value, and two patches possibly share a common value. I hope to fill in each patch a pattern according to its value. For instance, if a patch has value 1, then I fill in that patch

Bare test code: My simple Java test class source and R test code follow: public class RJavTest { public static void main(String[]args) { RJavTest rJavTest=new RJavTest(); } public final static String conStg="testString"; public final static double con0dbl=10000001; public final static double[]con1Arr=new double[] { 10001,10002,10003,10004,10005,10006 }; public final static

Hello, I have a couple questions regarding generalized linear mixed models specifically around fitting the random effects terms correctly to account for any pseudo-replication. I am reading through and trying to follow examples from Zuur et al. Mixed Effects Models and Extensions in Ecology with R, but am still at bit unsure if I am specifying the models correctly. Background information: Our

Recently I was trying to cite a package where the authors have ? and ? in their names. I found that on Windows the citation() function did not return the authors' names at all, but on Linux there was no problem (sessionInfos at the bottom): On Windows, no author names are returned: #--------------- > citation("readr") To cite package ?readr? in publications use: (2017).

hi, did'nt see anything in the archive: map('world',pro='rectangular',para=0) yields a strange artifact (horizontal bar) extending over the whole map at a certain latitude range (approx 65 deg. north), whereas map('world',pro='rectangular',para=180) (which should be the same) does not show the artifact. the artifact shows up in other projections as well,

Here is a patch for clustered xAPIC and Unisys ES7000 support in Xen. To turn the features on add CONFIG_X86_CLUSTERED_APIC and CONFIG_ES7000 defines to xen/include/asm-x86/config.h Signed off by Aravindh Puthiyaparambil <aravindh.puthiyaparambil@unisys.com> _______________________________________________ Xen-devel mailing list Xen-devel@lists.xensource.com

(I tried to send this earlier, but it doesnt seem to have come through, due to problems on my system) Hola: Both cannot be correct: > m <- matrix(1:4, 2) > svd(m) $d [1] 5.4649857 0.3659662 $u [,1] [,2] [1,] -0.5760484 -0.8174156 [2,] -0.8174156 0.5760484 $v [,1] [,2] [1,] -0.4045536 0.9145143 [2,] -0.9145143 -0.4045536 > La.svd(m) $d [1]

Hi there, i´m have vector of kernels. just like: kernels = c('gauss','epan','rectangular') i know there are density.default$kernels, but thats not my question here. my own kernel functions are running and working. my problem is the following is not working: dev.off() par(mfrow=c(3,3)) for(i in 1:length(bw)) { for(j in 1:length(kernels)) {

Hello. I have another rect question. If I want to make a lot of rectangular, without borders, and without any spaces between them, how could I do it? I.e. > plot(-1:1., -1:1., type = "n") > rect(0,-1,1,1,col="red",lwd=0,border=F,xpd=T) > rect(-1,-1,0,1,col="blue",lwd=0,border=F,xpd=T) will produce two rectangular, but there is space between them. How

Hi, I'm trying to do PCA on a n by p wide matrix (n < p), and I'd like to get more principal components than there are rows. However, svd() only returns a V matrix of with n columns (instead of p) unless the argument nv=p is set (prcomp calls svd without setting it). Moreover, the eigenvalues returned are always min(n, p) instead of p, even if nv is set: > x <-

Hello! I suppose this is more a matrix theory question than a question on R, but I will give it a try... I am using La.svd to compute the singular value decomposition (SVD) of a variance matrix, i.e., a symmetric nonnegative definite square matrix. Let S be my variance matrix, and S = U D V' be its SVD. In my numerical experiments I always got U = V. Is this necessarily the case? Or I might

--=====================_24736660==_ Content-Type: text/plain; charset="iso-8859-1"; format=flowed Content-Transfer-Encoding: quoted-printable SVD-Error on R 1.1.0 Windows 98 I get the following error applying svd on a positive definite matrix : > sk2 [,1] [,2] [,3] [,4] [,5] [1,] 1.0460139783 0.084356992 -2.810553e-04