similar to: left eigenvector

Check out textplot in the gregmisc package ... Federico Calboli <f.calboli@ucl.ac.uk> Sent by: r-help-bounces@stat.math.ethz.ch 07/13/2004 12:06 PM Please respond to f.calboli To: r-help <r-help@stat.math.ethz.ch> cc: Subject: [R] plotting a table together with graphs Dear All, I would like to ask how to add a table to a

[ This was posted to the R-packages list (which I moderate), but definitely doesn't belong there. Martin Maechler ] ------- start of forwarded message ------- From: Federico Calboli <f.calboli at ucl.ac.uk> To: r-packages at stat.math.ethz.ch Subject: how to upload Date: 15 Jul 2004 18:30:26 +0100 Dear All, I just finished a add on lib called Malmig, to calculate Malecot

Dear All, I would like to ask how to get the Sum of Squares from fitted lme model. I appreciate that lme maximises the likelihood (or REML) and uses likelihood ratio tests, but I just fail why I could not get the SS if I want them. I could use lm to calculate them, but it looks quite pointless to fit a second (and wrong in a way) model for something so trivial. I know that the issue has been

Dear All, I would like to ask how to customize the graph corresponding to a procrustes analysis. I have to distance matrices, that I transform to two set of coordinates by means of muti dimensional scaling: library(mva) c1<-cmdscale(mat.dist1) c2<-cmdscale(mat.dist2) I vant to rotate c2 on c1, and I use the "procrustes" analysis from the {vegan} library. library(vegan)

Dear All, I apologize if the following has been already asked, but I could not find anything in the archives. I am running Debian Sid (on an Athlon XP), with R 1.8.1.cvs.20040307-1 (it describes itself as "R 1.9.0 experimental" when I fire R up) and I am unable to load the library "nlme" (I apt-getted r-recommended, so the library is on the system) >library(nlme) Error in

> -----Original Message----- > From: Federico Calboli > Sent: Tuesday, January 20, 2004 5:40 PM > To: r-help > Subject: [R] matrix exponential: M^0 > > I would like to ask why the zeroeth power of a matrix gives me a matrix > of ones rather than the identity matrix: > > > D<-rbind(c(0,0,0),c(0,0,0),c(0,0,0)) > > D<-as.matrix(D) > > D >

Dear All, I am in the somewhat unfortunate position of having to reproduce the results previously obtained from (non-metric?) MDS on a "kinship" matrix using Statistica. A kinship matrix measures affinity between groups, and has its maximum values on the diagonal. Apparently, starting with a nxn kinship matrix, all it was needed to do was to feed it to Statistica flagging that the

Dear all, I am putting together a business case for R and I would like to know if there exist statistics on the distribution of R in academia, research and commercial institutions. The same information about S-plus would be welcome. Please reply only if you have consistent and certain information. Thank you very much, giovanni

I am using a two-factor ANOVA model with random factor effects including the interaction, i.e. the factors are crossed. I would like to be able to generate all four variance components along with approximate confidence intervals using the NLME package. However, I do not know how to specify the random option because of two problems. First, I do not know how to enter the interaction term into the

Dear all, We compared the gene expression level in two conditions: high (H) and low (L), using real-time PCR. We had 3 samples of each condition, and we quantified each sample twice (i.e. a technical replication). Our data looks like: H1 H1 H2 H2 H3 H3 L1 L1 L2 L2 L3 L3 We want to test if the level in H vs L is significantly different. I would like to use ANOVA and I guess a nested model with

Hello everybody, I'm seeing some strange behavior on R 1.8.1 on Intel/Linux compiled with gcc 3.2.2. The p-value calculated from the chisq.test function is incorrect for some input values: > chisq.test(matrix(c(0, 1, 1, 12555), 2, 2), simulate.p.value=TRUE) Pearson's Chi-squared test with simulated p-value (based on 2000 replicates) data: matrix(c(0, 1, 1,

How about this: > expm function(x,pow=2) { xd <- diag((eigen(x)$values^pow)) xm <- eigen(x)$vector %*% xd %*% t(eigen(x)$vector) return(xm) } > xa [,1] [,2] [1,] 2 1 [2,] 1 3 > expm(xa,pow=3) [,1] [,2] [1,] 15 20 [2,] 20 35 > xa %*% xa %*% xa [,1] [,2] [1,] 15 20 [2,] 20 35 > From: Federico Calboli <f.calboli at ucl.ac.uk>

I use linux debian testing for which the latest debianized version of R is 1.8.1. Therefore I installed: r-base-core_1.8.1-0.cran.1_i386.deb r-base-dev_1.8.1-0.cran.1_all.deb r-base-html_1.8.1-0.cran.1_all.deb r-base-latex_1.8.1-0.cran.1_all.deb r-base_1.8.1-0.cran.1_all.deb r-doc-html_1.8.1-0.cran.1_all.deb r-doc-info_1.8.1-0.cran.1_all.deb

Dear All, I would like to ask if there is any package that would calculate Malecot migration matrix (or the Imaizumi or Pena implementations of the MMM). I did a site-wide search, and went trough the table of contents of a number of packages that seemed promising, but with no luck. Regards, Federico Calboli -- ================================= Federico C. F. Calboli PLEASE NOTE NEW

Dear all, I would like to ask you the following: I have data about different manuscripts, together with data about the presence/absence of copying errors, in the days when manuscript were really manuscripts. I would ideally like to use the data to draw a phylogenetic tree, so that I can infer which ms was copied from which. The error presence/absence is coded in binary format. The plan is to use

Hi, If I use the eigen() function to find the eigenvalues of a matrix, how can I find the eigenvector corresponding to the largest eigen value? Thanks! [[alternative HTML version deleted]]

Hello alls, I found in the literature a technique that has been evaluated as one of the more robust to assess statistically the significance of the loadings in a PCA: bootstrapping the eigenvector (Jackson, Ecology 1993, 74: 2204-2214; Peres-Neto and al. 2003. Ecology 84:2347-2363). However, I'm not able to transform by myself the following steps into a R program, yet? Can someone could help

G'Day R users! Following an ordination using prcomp, I'd like to test which variables singnificantly contribute to a principal component. There is a method suggested by Peres-Neto and al. 2003. Ecology 84:2347-2363 called "bootstrapped eigenvector". It was asked for that in this forum in January 2005 by J?r?me Lema?tre: "1) Resample 1000 times with replacement entire

Dear All i have a little puzzle about eigenvector in the R. As we know that the eigenvector can be displayed on several form. For example A=matrix(c(1,2,4,3),2,2) if we want to get the eigenvalue and eigenvector, the code followed eigen(A) $values [1] 5 -1 $vectors [,1] [,2] [1,] -0.7071068 -0.8944272 [2,] -0.7071068 0.4472136 however, we also can calculate the vector matrix

Dear all I am so glad the R can provide the efficient calculate about eigenvector and eigenvalue. However, i have some puzzle about the procedure of eigen. Fristly, what kind of procedue does the R utilize such that the eigen are obtained? For example, A=matrix(c(1,2,4,3),2,2) we can define the eigenvalue lamda, such as det | 1-lamda 4 | =0 | 2 3-lamda | then