similar to: detecting singular matrices

I have a small handheld pc having ARM process as a CPU. I installed debian and installed R using apt-get command. Everything worked great except for drawing even simple graphs x <- 1:10 plot(x) I got error messages 1: Nonfinite axis limits [GScale(nan,nan,1, .); log=0] 2: relative range of values = 9.0072e+15 * EPS, is small (axis 1). 3: Nonfinite axis limits

I post this message on R-help mailing list but someone emailed me that I can get helped if I post this one on R-devel mailing list. I have a small handheld pc having ARM process as a CPU. I installed debian and installed R (R-1.7.0 base and core, help html, latex-help) using apt-get command. Everything worked great except for drawing even simple graphs x <- 1:10 plot(x) I got error

Debian tries to build its packages on a variety of platforms. The arm platform compiled 0.90.1 (the last Debian release before the Debian package required an Atlas library, something we no longer require) failed in 'make check'. The log snippet follows; I traced this to the example(Bessel) code. > matplot(nu, t(outer(xx,nu, besselI)), type = 'l', ylim = c(-50,200), +

Hello everyone When asking to create sequence longer than 2^48 (which is forbidden) the same error message appears translated and untranslated depending on whether R_XLEN_T_MAX is reached or exceeded while not an error o problem beyond that of the untranslated text, i find this weird. ?could it be fixed in any manner? R_XLEN_T_MAX <- 4503599627370496 > length(1:(R_XLEN_T_MAX - 1)) [1]

I''ve demoed my rails app and now have to move it to a MSSQL DB. the big problem I''m running into is the table name conventions I have to use. I have to use names like tbl_Transfer & tbl_User. In my tests on the console, I am trying myvar = tbl_Transfer.find_by_sql("select top 1 * from tbl_Transfer") NameError: undefined local variable or method

[using RAILs 1.1.2] Has anyone else seen issues where multiple tiered "acts_as_list" models do not CASCADE delete correctly? For instance, I have 4 models, the first 3 in the hierarchy have the appropriate "have_many" declarations with "exclusively_dependent => true". The last the models have the appropriate "acts_as_list" with the correct scope

I just got this error: uninitialized constant PriceCurf After much head scratching I remembered the Rails plural to singular mapping rules. My table is price_curves, my object is PriceCurve ... whereas I am guessing Rails thinks the singular ought to br PriceCurf ?! I''m sure there is a simple way around this linguistic blunder that doesn''t involve the use of pigeon English.

Dear all, I am using the plm package for both fixed and random effects models on my country-year panel data. However, for some of the random effects models I get the following error: Error in solve.default(OM) : system is computationally singular: reciprocal condition number = 1.78233e-18 The same models work fine for fixed effects. I have also noticed that once I remove some of my variables

Does anyone know of any tools to do multichannel(multivariate) singular spectrum analysis (M-SSA) in R? Seems like this would be a useful thing to have. -Hilbert [[alternative HTML version deleted]]

With a matrix such as C I do not have any problem: >library(gmp) > C V1 V2 V3 V4 V5 V6 V7 [1,] 1 0 0 0 1 0 0 [2,] 0 1 0 0 0 1 0 [3,] 0 0 1 0 0 0 1 [4,] 0 0 0 1 0 0 0 [5,] 0 0 0 0 1 0 0 [6,] 0 0 0 0 0 1 0 [7,] 0 0 0 0 0 0 1 > solve.bigz(C) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [1,] "1" "0" "0"

Hello, i'm tring to use a cox's model for a survival analysis. I have a dataset, this is a part: VOD SESSO fonte_sct donor RT_CGY STATOBMT TEMPO morto 1 0 F mid related 1200 CP 65 1 2 0 M mid 1200 2RC 5281 0 3 0 M mid unrelated 1200

Hi everybody! I am searching for an R implementation of multi-scale SSA (singular spectrum analysis), which was introduced by Yiou etal (2000) (Data-adaptive wavelets and *multi*-*scale *singular-spectrum analysis<http://linkinghub.elsevier.com/retrieve/pii/S0167278900000452>) and further described in Ghil etal (2002). For SSA alone I found an package recently published on r-forge:

Hi, I have the followed Rails 3 routes: Hello::Application.routes.draw do resources :blogs do resources :articles do resources :comments end end end By raking them, we can find (for instance): GET /blogs/:blog_id/articles(.:format) {:action=>"index", :controller=>"articles"} Because every routes begin with the

Are there any functions available to do a factor analysis with fewer observations than variables? As long as you have more than 3 observations, my computations suggest you have enough data to estimate a factor analysis covariance matrix, even though the sample covariance matrix is singular. I tried the naive thing and got an error: > set.seed(1) > X <- array(rnorm(50), dim=c(5,

Dear R-users, I recently used factanal function in mva library to perform factor analysis. I notice that the function will give an error message that the log likelihood function is infinite whenever the observed covariance matrix is singular. This is because the function uses multivariate normal log-likelihood which involve log determinant of the observed covariance matrix. But I wonder if the

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,

This should be easy to solve; I''m trying to get an Rspec routing_spec working with a singular nested resource; map.resources :users do |user| user.resource :profile end All the tests in the profile_routing_spec seem to be failing because they can''t match the routes, for example; # The spec describe ProfileController do describe "route generation" do it

Hi All, I'm trying to estimate some parameters in my model via GMM using the function gmm(), but I keep getting the message "The covariance matrix of the coefficients is singular". I've changed the moment conditions and the initial value of the parameters, and I still get this message. Are the results valid after receiving this message? Any ideas on how to get rid of it?

I tried to fit data with the following function: fit<-nls(y~ Is*(1-exp(-l*x))+Iph,start=list(Is=-2e-5,l=2.3,Iph=-0.3 ),control=list(maxiter=500,minFactor=1/10000,tol=10e-05),trace=TRUE) But I get only a singular Gradient warning... the data can by found attached(there are two sampels of data col 1/2 and 3/4). I tried to fix it by chanching the start parameters but that didn't solve the

Hi wizards, I have seen the function svd of R for singular value decomposition, but I need to computes the ``economy size'' or ``thin'' singular value decomposition of a matrix in R. Somebody knows how to do that?. Thanks in advance. -- Web Page http://geocities.com/lord_tyranus_96/