similar to: info : Manova - eigenvector analysis and canonical analysis

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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]]

Hi everybody, I need help in writing a statistical function for bootstrap. Suppose m is a matrix with n cols and p rows, my original data. What I want to do is a bootstrap (using boot from package boot) on eigenvectors from a PCA done on m with a statistic function calculating the eigenvector bootstrap error ratio. If R = number of bootstrap replicates, then my function should look something

Hi to all, I have two graphs with the same number of nodes but with different connectivities and also with a different number of clusters. The two graphs represent the same "system" under different "conditions" and then there is a one-to-one correspondence between a given node in the two graphs. It is correct to use the eigenvector centrality score as a measure of the relevance

Hello all, I was wondering if there is a function in R that only computes the eigenvector corresponding to the largest/smallest eigenvalue of an arbitrary real matrix. Thanks Minh -- Living on Earth may be expensive, but it includes an annual free trip around the Sun.

Dear All, how do I compute the left eigenvector of a matrix? I gather that "eigen" computes the right eigenvectors... Regards, Federico Calboli -- ================================= Federico C. F. Calboli PLEASE NOTE NEW ADDRESS Dipartimento di Biologia Via Selmi 3 40126 Bologna Italy tel (+39) 051 209 4187 fax (+39) 051 251 208 f.calboli at ucl.ac.uk

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

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

Some of you may have seen a message on s-news by Stefan Steinhaus regarding his paper on "Comparison of mathematical programs for data analysis". He compares S-PLUS 4.5 with several other programs. He does not include R in the comparisons. On p. 28 of his report he gives the URL the Auckland site along with URL's for two other systems but comments that "I didn't received

Dear R users & Experts, This is just a curiousity, I was wondering why the dominant eigenvetor and eigenvalue of the following matrix is given as the third. I guess this could complicate automatic selection procedures. 0 0 0 0 0 5 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 Please

Hey, All In principal component analysis (PCA), we want to know how many percentage the first principal component explain the total variances among the data. Assume the data matrix X is zero-meaned, and I used the following procedures: C = covriance(X) %% calculate the covariance matrix; [EVector,EValues]=eig(C) %% L = diag(EValues) %%L is a column vector with eigenvalues as the elements percent

Hi, there, I am using PC window version R and dealing with big dataset usually. May anyone let me whether the maximal dataset size in R is limited by computer memory or hard drive capacity? Thanks in advance. Yiling Cheng, M.D., Ph.D. Project Manager The Cooper Institute for Aerobics Research 12330 Preston Road, Dallas, Texas 75230 phone: (972) 3413248; Fax: (972) 3413224

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

Hello R-users. I believe that the way basehaz (in the survival package) compute the baseline hazard function is false. I come to question this function when it gives me hazard probabilities greater than 1. Looking at the code I think I've localised the error : hazard probability is computed as : H <- -log(surv) but it seems to me that hazard probabilities is rather an instantaneous

On 23.11.2012, at 15:12, john skaller <skaller at users.sourceforge.net> wrote: > > On 23/11/2012, at 5:46 PM, Sean Silva wrote: > >> Adding LLVMdev, since this is intimately related to the optimization passes. >> >>> I think this is roughly because some function level optimisations are >>> worse than O(N) in the number of instructions. >>