similar to: Matrix package,solve() errors and crashes Please help

Hello All, I am working on graph object using IGRAPH package wanted to do Bonacich Power. This is my graph object. The file 'Graph.RData' (4.2 MB) is available for download at http://dropbox.unl.edu/uploads/20090424/cfe4fcb854bb17f2/Graph.RData Graph size Vertices: 20984 Edges: 326033 Directed: FALSE No graph attributes. Vertex attributes: name. No edge attributes. When I use

Hello All, I am working on graph object using IGRAPH package wanted to do Bonacich Power. This is my graph object. The file 'Graph.RData' (4.2 MB) is available for download at http://dropbox.unl.edu/uploads/20090424/cfe4fcb854bb17f2/Graph.RData Graph size Vertices: 20984 Edges: 326033 Directed: FALSE No graph attributes. Vertex attributes: name. No edge attributes. When I use

Hello All, I have been trying to do bonpow for a while now.Bonpow works for few graphs and for few others it goes out of memory. I did see reply to one of the posting Alph Centrality Crashed in Igraph memory error. The solution in the posting was to use sparse matrix. This is the link of the message. http://lists.gnu.org/archive/html/igraph-help/2008-04/msg00071.html I was able to obtain

Hi All, This is my R-version information:--- > version _ platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 7.1 year 2008 month 06 day 23 svn rev 45970 language R version.string R version 2.7.1 (2008-06-23) While calculating partial

Hi: I have data from an assay in the form of two vectors, one is response and the other is a predictor. When I attempt to fit a 5 parameter logistic model with "nls", I get converged parameter estimates. I also get the same answers with "gnls" without specifying the "weights" argument. However, when I attempt to use the "gnls" function and try to

Hello, does anybody know another faster function for random multivariate normal variable simulation? I'm using mvrnorm, but as profiling shows, my algorithm spends approximately 50 % in executing mvrnorm function. Maybe some of you knows much faster function for multivariate normal simulation? I would be very gratefull for advices. -- View this message in context:

Hello, I have a short question about the prcomp function. First I cite the associated help page (help(prcomp)): "Value: ... SDEV the standard deviations of the principal components (i.e., the square roots of the eigenvalues of the covariance/correlation matrix, though the calculation is actually done with the singular values of the data matrix). ROTATION the matrix of variable loadings

Dear R-community, Using bwplot, how can I put the whiskers at percentile 5 and percentile 95, in place of the default position coef=1.5?? Using panel=panel.bwstrip, whiskerpos=0.05, from the package agsemisc gives satisfaction, but changes the appearance of my boxplot and works with an old version of R, what I don’t want, and I didn’t find the option in box.umbrella parameters Many thanks

I get this error while computing partial correlation. *Error in solve.default(Szz) : system is computationally singular: reciprocal condition number = 4.90109e-18* Why is it?Can anyone give me some idea ,how do i get rid it it? This is the function i use for calculating partial correlation. pcor.mat <- function(x,y,z,method="p",na.rm=T){ x <- c(x) y <- c(y)

Hello. Somebody knows how can I generate a set of n random vectors of a normal distribution of several variables? For example, I want to generate n=100 random vectors of two dimensions for a normal with mean c(0,1) and variance matrix: matrix(c(2,1,1,3),2,2). Thanks in advance, Arnau.

I have been told by the CRAN administrators that the following code generated an error on 64-bit Fedora Linux (gcc, clang) and on Solaris machines (sparc, x86), but runs well on all other systems): > fn <- function(x, y) ifelse(x^2 + y^2 <= 1, 1 - x^2 - y^2, 0) > tol <- 1.5e-8 > fy <- function(x) integrate(function(y) fn(x, y), 0, 1,

Hello, I am trying to find the analytical solution to this differential equation dR/dt = k1*(R^k2)*(1-(R/Rmax)); R(0) = Ro k1 and k2 are parameters that need to fitted, while Ro and Rmax are the baseline and max value (which can be fitted or fixed). The response (R) increases initially at an exponential rate governed by the rate constants k1 and k2. Response has a S-shaped curve as a function

Estimados Usuarios-R: Estoy convirtiendo un programa en Matlab a R. El original lo saqu de: Lai, M., & Poltera, Y. (2009). Lecture with computer exercises: Modelling and simulating social systems with matlab. Tech. rep., Swiss Federal Institute of Technology (December 2009). 27. Ahora estoy convirtiendo la siguiente funcin: function sizes = gridsizes(N,varargin) % gridsizes(N) calculates

Resending this as the message size limit for the list is 100 KB, and uncompressed, the attached plugin code is 150 KB. ---------- Forwarded message ---------- Date: Thu, 12 Oct 2006 23:47:25 +0300 (EEST) From: Tuukka Hastrup <Tuukka.Hastrup@iki.fi> To: Mike Dransfield <mike@blueroot.co.uk> Cc: compiz@lists.freedesktop.org Subject: Re: [compiz] Privates example? On Thu, 12 Oct 2006,

Hello everyone I am trying to get one of my packages through R's QC. The package is clean for me under R-2.4.1, R-2.5.0, and R-devel, but Kurt gets > > * checking R code for possible problems ... WARNING > hypercube: no visible binding for global variable ?f? Function hypercube() [cut-&-pasted below] is intended to return an adjacency matrix for an n-dimensional

Hi, I'm trying to compile two functions into one function. the first funtion is called 'fs' which is self-made function, another function is from the built-in 'integration' function that is copy-paste-edited. If built separatey, these functions work well. However that is not the case if combines together, where certainly I made mistake somewhere when constructing the code.

I'm a week-old R user, and have become stuck trying to create usable CSV outputs for post-processing. I am using the package Rioja, which provides small datasets of results. I am running several analyses in a loop and iteratively adding the results to a *list* ("combined"). Within each iteration I use the following: > combined[[i]] <- performance(fit) With two iterations I

I was trying to find source for optimize and I ran across function (f, interval, ..., lower = min(interval), upper = max(interval), maximum = FALSE, tol = .Machine$double.eps^0.25) { if (maximum) { val <- .Internal(fmin(function(arg) -f(arg, ...), lower, upper, tol)) list(maximum = val, objective = f(val, ...)) } else { val <-

G'day all, I have daily scripts running to install the patched version of the current R version and the development version of R on my linux box (Ubuntu 18.04.2 LTS). The last development version that was successfully compiled and installed was "R Under development (unstable) (2019-02-25 r76159)" on 26 February. Since then the script always fails as a regression test seems to

Two friend reported me a problem, which I can't solve: (I run R-1.0.0, Debian Linux) They hava a function "corr.matrix" (see end of mail), and when they create a 173x173 matrix with this function V <- corr.matrix(0.3, n=173) V1 <- qr.solve(V) reports: Error in qr(a, tol = tol) : NA/NaN/Inf in foreign function call (arg 1) For n < 173, qr.solve returns the correct