similar to: R analog of Matlab "eigs" function

Hello Does anybody know how one can compute d largest eigenvalues/eigenvectors in R, like in MATLAB eigs function ? eigen function computes all eigenvectors/eigenvalues, and they are slightly different than those generated by matlab eigs. Thanks in advance -- View this message in context: http://www.nabble.com/matlab-eigs-function-in-R-tp17619641p17619641.html Sent from the R help mailing list

Dear all, I want to compute the eigenvalues of a complex matrix for some statistics. Comparing it to its matlab/octave sibling, I don't get the same eigenvalues in R computing it from the exact same matrix. In R, I used eigen() and arpack() that give different eigenvalues. In matlab/octave I used eig() and eigs() that give out the same eigenvalues but different to the R ones. For real

Dear R-listers Is there anyone who knows why I get different eigenvectors when I run MatLab and R? I run both programs in Windows Me. Can I make R to produce the same vectors as MatLab? #R Matrix PA9900<-c(11/24 ,10/53 ,0/1 ,0/1 ,29/43 ,1/24 ,27/53 ,0/1 ,0/1 ,13/43 ,14/24 ,178/53 ,146/244 ,17/23 ,15/43 ,2/24 ,4/53 ,0/1 ,2/23 ,2/43 ,4/24 ,58/53 ,26/244 ,0/1 ,5/43) #R-syntax

Dear R-help list, I have a problem storing results from a bootstrap loop. What I doing is creating an empty matrix before the loop, then run the loop. Before the end of the loop I have a command line which defines which results inside the loop will have to go in the empty matrix. Here is the code I am using: eigen.values<-rep(NA,boots) #storage file for eigen values (1 for simulation)

Dear all, I am currently working on the calculation of eigenvalues (and -vectors) of large matrices. Since these are mostly sparse matrices and I remember some specific functionalities in MATLAB for sparse matrices, I started a research how to optimize the calculation of eigenvalues of a sparse matrix. The function eigen itself works with the LAPACK library which has no special handling for

Hi, I was wondering if function eigen() does something different from the function call eigen() in SAS. I'm in the process of translating a SAS code into a R code and the values of the eigenvectors and eigenvalues of a square matrix came out to be different from the values in SAS. I would also appreciate it if someone can explain the difference in simple terms. I'm pretty new to both

Which function implements the piecewise cubic Hermite interpolation? I am looking for equivalent of matlab's interp1 with the method = 'pchip' Here is the reference http://www.mathworks.com/access/helpdesk/help/techdoc/index.html?/access/helpdesk/help/techdoc/ref/interp1.html& -- View this message in context:

igraph is a package for graphs and networks. It has a C core and uses a simple and fast graph representation allowing millions of vertices and edges. NEW FEATURES: - We use the ARPACK library for graph related eigenvalue problems, like Page Rank calculation, Kleinberg's hub and authority scores, eigenvector centrality, etc. There is also a generic interface if someone wants to use

igraph is a package for graphs and networks. It has a C core and uses a simple and fast graph representation allowing millions of vertices and edges. NEW FEATURES: - We use the ARPACK library for graph related eigenvalue problems, like Page Rank calculation, Kleinberg's hub and authority scores, eigenvector centrality, etc. There is also a generic interface if someone wants to use

DeaR list, I happily use eigen() to compute the eigenvalues and eigenvectors of a fairly large matrix (200x200, say), but it seems over-killed as its rank is limited to typically 2 or 3. I sort of remember being taught that numerical techniques can find iteratively decreasing eigenvalues and corresponding orthogonal eigenvectors, which would provide a nice alternative (once I have the

Hi, I'm trying to use R to get eigenvalues and eigenvectors of a matrix whose elements are of the form (2 * lambda), -(lambda + mu), etc. I'd like R to treat this matrix as a numeric matrix without treating lambda and mu as variable names but rather as some sort of atomic quantities (and hence give eigenvectors in terms of mu and/or lambda). MatLab and Mathematica both do this,

Hi I need to extract the data returned by Eigen to plot the eigenvectors. However, when I try and eigv = eigen(covariance); it returns an object with the matrices containing eigenvalues and vectors.. how can I extract the eigenvector matrix from this?? When I try mat = eig["vectors"] it returns a matrix with the "$vectors" string on top , how can I remove this? code: > eig

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.

> Background: > OS: Linux Mandrake 9.1 > release: R 1.9.0 > editor: Xemacs 21.4 > frontend: ESS 5.1.23 > --------------------------------- > > Colleagues > Is there a function in R that is similar to polyval in matlab? (y = polyval(p,x) returns the value of a polynomial of degree n evaluated at x. The input argument p is a vector of length n+1 whose elements are the

Dear R users I?m aware that the package ?modest? is useful to find the mode in an array. However, I?d like to know if someone has translated the ?mode? function built-in in MATLAB into R language. This function finds the most frequent value in an array (http://www.mathworks.com/help/techdoc/ref/mode.html). Best Fer

hi, all I am looking at R package RGL to draw a colored mesh/surface plot like this one (from matlab). http://www.mathworks.com/access/helpdesk/help/techdoc/visualize/cbar.gif The key features I am looking for is surfaced with grid and color, but not the terrain-like gradient. but I didn't come even close to it after browsing through rgl help file. have anyone drawn something like this

Hi, I am having trouble with some code that I am dyn.loading. I am writing an interface to ARPACK. I compile my interface (dssimp.cc), and link it against the ARPACK library (libarpack_SUN4.a): g++ -shared -static -fPIC dssimp.cc -o dssimp.so -larpack_SUN4 -lg2c -lm I can dyn.load the code and it appears OK. However, when I call my function, the call to the function in the ARPACK library

I would like to efficiently find the first index of each unique value in a very large vector. For example, if I have a vector A<-c(9,2,9,5) I would like to return not only the unique values (2,5,9) but also their first indices (2,4,1). I tried using a for loop with which(A==unique(A)[i])[1] to find the first index of each unique value but it is very slow. What I am trying to do is easily

Full_Name: Yves Rosseel Version: 2.2.1 OS: Submission from: (NULL) (157.193.116.152) The code below sketches a possible implementation of a function 'mlh.mlm' which I think would be a good complement to the 'anova.mlm' function in the stats package. It tests a single linear hypothesis of the form H_0: LBT'= 0 where B is the matrix of regression coefficients; L is a matrix

Try something like: install.packages("polynom") library(polynom) predict(polynomial(rev(p)), x) HTH, Andy > From: McClatchie, Sam (PIRSA-SARDI) > > > Background: > > OS: Linux Mandrake 9.1 > > release: R 1.9.0 > > editor: Xemacs 21.4 > > frontend: ESS 5.1.23 > > --------------------------------- > > > > Colleagues > >