similar to: System is computationally singular and scale of covariates

Dear all, sorry, this is for sure really basic, but I searched a lot in the internet, and just couldn't find a solution. The problem is to create new variables from a data frame which contains both individual and group variables, such as mean age for an household. My data frame: df hhid h.age 1 10010020 23 2 10010020 23 3 10010126 42 4 10010126 60 5 10010142

Dear all, I have a simple question which I unfortunately do not seem to be able to solve myself. I have a (NxK) matrix and want to generate a new matrix by multiplying each row with itself such that the new matrix has dimension ((N*K)xK) (or better, generate an array with dimension (K,K,N)). I tried apply, but that did not work. Any suggestions? Thanks! Stephan ## Here is a simple

Dear all, I have a code where I subset a data frame to match entries within levels of an factor (actually, the full script uses three difference factors do do that). I'm very happy with the precision with which I can work with R, but since I loop over factor levels, and the data frame is big, the process is slow. So I've been trying to speed up the process using by(), but I got stuck at

Dear all, A quick question which I somehow cannto figure out: I want to apply the function "any" to subsets of a dataset in order to create a vector with TRUE/FALSE values, depending on whether a subset has the number 5. I.e., y <- matrix(c(1,2,3,3,4,5,5,6,6,7,5,1,1,3,5,NA,5,1,1,3),ncol=2) > y [,1] [,2] [1,] 1 5 [2,] 2 1 [3,] 3 1 [4,] 3 3 [5,]

Dear all, I'm trying to import a csv file into sqlite3 and from there into R. Everything looks fine exepct that R outputs the character values in an odd fashion: they are shown as "\"CHARACTER\"" instead of "CHARACTER", but only if I show the character variable as a vector. Does someone know why this happens? Below is a sample code. The first part is written in

Dear R-help, I'm very sorry to ask 2 questions in a week. I am using the package 'crr' and it does exactly what I need it to when I use the dataset a. However, when I use dataset b I get the following error message: Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) : system is computationally singular: reciprocal condition number =

Dear expe-R-ts, I try some test data for a factorAnalysis (resp. pca) in the sense of Prof. Ripley's MASS ? 11.1, p. 330 ff., just to prepare myself for an analysis of my own empirical data using R (instead of SPSS). 1. the data. ## The test data is (from the book of Backhaus et al.: Multivariate ## Analysemethoden. Springer 2000 [9th ed.], p. 300 ff):

Hi. I'd like to find some way for Samba to convert the filenames created by Macintosh OS X into something windows can use. According to their docs: http://developer.apple.com/techpubs/macosx/Essentials/SystemOverview/FileSystem/chapter_9_section_13.html filenames are stored as canonically decomposed Unicode 2.1 in UTF-16 format (a sequence of 16-bit codes) Samba running on a

Dear all, just a quick question regarding weights in logistic regression. I do results <- lrm(y.js ~ h.hhsize + h.death1 + h.ill1 + h.ljob1 + h.fin1 + h.div1 + h.fail1 + h.sex + h.ch.1

i was using multiple ports because that's how i figured i'd have to do it. o, mounting the remote source locally? i'm not familiar with how to do this. i'm also not seeing how to do this in the docs. how would i go about mounting a remote stream? -a.j. On Fri, 27 Apr 2001, Jack Moffitt wrote: > Why are you using multiple ports at all? That's what mountpoints are >

Hi, I am estimating a regression but the summary command is unable to provide me results, while the coefficients are available from the coefficients value. I suppose that it cannot estimate the covariance matrix. Is there any command that I can relax the tolerance so it can estimate the covariance matrix. The code and the error of R is: eq1<-rq(y~factor(year)+factor(state)+x1+x2+x3,

Dear R users, i try to use function dmvnorm(x, mean, sigma, log=FALSE) from R package mvtnorm to calculate the probability of x under the multivariate normal distribution with mean equal to mean and covariance matrix sigma. I become the following Error in solve.default(cov, ...) : system is computationally singular: reciprocal condition number = 1.81093e-19 What could be the reason of it?

Hi uRsers, when inverting a 2 by 2 matrix using solve, I encountered a error message: solve.default(sigma, tol = 1e-07) : system is computationally singular: reciprocal condition number = 1.7671e-017 and then I test the determinant of this matrix: 6.341393e-06. In my program, I have a condition block that whether a matrix is invertible like this: if(det(sigma)<1e-7) return NULL;

Hi all, I was using the Newton-Raphson method to estimate paremeters in the model developed by my supervisor. However, when I interatively computed theta(t+1)=theta(t) - solve(H)*s (where the Hessian matrix and score vector were explicitely derived), I got the error message: Error in solve.default(H) : system is computationally singular: reciprocal condition number = 1.70568e-032. Assume my score

Hi folks, I know, this is a fairly common question and I am really disappointed that I could not find a solution. I am trying to calculate Mahanalobis distances in a data frame, where I have several hundreds groups and several hundreds of variables. Whatever I do, however I subset it I get the "system is computationally singular: reciprocal condition number" error. I know what it means

Hi, I have tried to install 'tensor' as a new package in these phases: 1. via 'Install package from local Zip-File' in Rgui/Windows98: install.packages("D:/R/_Pakets12MB/tensor.zip", .lib.loc[1], CRAN = NULL) 2. Looking at the library folder, there was now a new entry 'tensor' including some files e.g. \library\tensor\R\tensor.R 3. Then I have done

heya... i'm extremely new to the list (10 minutes), and i have a burnin' question that i was hopin' you folks could help me out with. i'm running beos as an encoder box, with two streams (8000 and 8001) hosted on it. the idea is to use my redhat box to relay those streams to the public using icecast, allowing the be machines cpu cycles to focus solely on encoding. anyway, i

Hi all, I am trying to set up a simple path analysis in the SEM package, but I am having some trouble. I keep getting the following error message or something similar with my model, and I'm not sure what I'm doing wrong: Error in solve.default(C) : system is computationally singular: reciprocal condition number = 2.2449e-20 In addition: Warning message: In sem.default(ram = ram, S = S,

Hi, I have a dataset which has around 138 variables and 30,000 cases. I am trying to calculate a mahalanobis distance matrix for them and my procedure is like this: Suppose my data is stored in mymatrix > S<-cov(mymatrix) # this is fine > D<-sapply(1:nrow(mymatrix), function(i) mahalanobis(mymatrix, mymatrix[i,], S)) Error in solve.default(cov, ...) : system is computationally

Dear, I built the generalized method of moments model to estimate the sales rank in the bookstore using plm package in R. The equation is: data1.gmm <- pgmm(dynformula(lnsales_rank ~ ln_price + avg_ham_rate + avg_spam_rate + num_of_ham+ num_of_spam + ship_code2 +ship_code3 +ship_code4+ ship_code5+ ship_code6 + ship_ code7, lag = list(0, 0, 0, 0,0,0,0,0,0,0,0,0), log =FALSE), data=data,