search for: singular

Hello, I'm using the gstat package within R for an automated procedure that uses ordinary kriging. I can see that there is a logical ("singular") atrtibute of some adjusted model semivariograms: .- attr(*, "singular")= logi TRUE I cannot find documentation about the exact meaning and the implications of this attribute, and I dont know anything about the inner calculations of model semivariograms. I guess that the inverse...

Hi all I'm facing an issue while running dovecot inside a singularity (https://sylabs.io/singularity/) container dovecot version is 2.3.4.1 (configuration below) running on debian buster, inside a container made with singularity version 3.4.2 unfortunately, when I try to start dovecot, it gives: Singularity test.sif:~> cat /var/log/mail.log Dec 30 17:23:38 te...

...; target.utt / prime.utt , family=binomial(link = "logit"), > data=data.utts, niter=5, verbose = TRUE) > Loading required package: nlme > iteration 1 > iteration 2 > iteration 3 > Error in solve.default(pdMatrix(a, fact = TRUE)) : > system is computationally singular: reciprocal condition > number = 8.65949e-32 > In addition: Warning messages: > 1: Singular precision matrix in level -1, block 4 > 2: Singular precision matrix in level -1, block 4 > 3: Singular precision matrix in level -1, block 4 > 4: Singular precision matrix in level -1, b...

...poisson, data=tab), What I want to do is to see if number of recruits (a) is dependent on the brood sex ratio (b) including brood identity (c) as random factor. However, I get the following error message; lmer(a~b + (1|c), family=poisson, data=tab) Error in devAGQ(PQLpars, 1) : Unable to invert singular factor of downdated X'X In addition: Warning messages: 1: optim or nlminb returned message singular convergence (7) in: LMEopt(x = mer, value = cv) 2: optim or nlminb returned message singular convergence (7) in: LMEopt(x = mer, value = cv) 3: optim or nlminb returned message singular con...

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; but this seems doesnot work to prevent the singularity when invert...

Dear R, If I have remembered correctly, a square matrix is singular if and only if its determinant is zero. I am a bit confused by the following code error. Can someone give me a hint? > a <- matrix(c(1e20,1e2,1e3,1e3),2) > det(a) [1] 1e+23 > solve(a) Error in solve.default(a) : system is computationally singular: reciprocal condition number = 1e-17...

...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 and I know what should be the problem, but there is no way this is a singular matrix. I have uploaded the input file to my ftp: http://mkk.szie.hu/dep/talt/lv/CentInpDuplNoHeader.txt It is a tab delimited txt file with no headers. I...

...t; on Thu, 14 Sep 2017 10:13:02 +0200 writes: >>>>> Fox, John <jfox at mcmaster.ca> >>>>> on Wed, 13 Sep 2017 22:45:07 +0000 writes: >> Dear Terry, >> Even the behaviour of lm() and glm() isn't entirely consistent. In both cases, singularity results in NA coefficients by default, and these are reported in the model summary and coefficient vector, but not in the coefficient covariance matrix: >> ---------------- >>> mod.lm <- lm(Employed ~ GNP + Population + I(GNP + Population), >> +...

//Referring to the response posted many years ago, copied below, what is the specific criterium used for singularity of the gradient matrix? Is a Singular Value Decomposition used to determine the singular values? Is it the gradient matrix condition number or some other criterion for determining singularity? // //Glenn // / / /> What does the error 'singular gradient' mean during a nonlinea...

Hi everyone. I'm working with nlme and I have a question regarding nlme fits that fail because of singularity issues. Specifically, there a way to return an nlme object when the estimation process runs into a singular matrix? For example, can the results up to the point of an error such as "Error in solve.default(pdMatrix(a, fact = TRUE)) : system is computationally singular" or "Error in...

>>>>> Fox, John <jfox at mcmaster.ca> >>>>> on Thu, 14 Sep 2017 13:46:44 +0000 writes: > Dear Martin, I made three points which likely got lost > because of the way I presented them: > (1) Singularity is an unusual situation and should be made > more prominent. It typically reflects a problem with the > data or the specification of the model. That's not to say > that it *never* makes sense to allow singular fits (as in > the situations you mentions). >...

...selection for a multiple linear regression using function lm and update. But, I meet a problem when using update. The problem is the function update can not update when variables as a vector(for example,x is a matrix with 100 regression variables). The code is as below: > model<-lm(y~x1,singular.ok=T,na.action=na.omit) > for(i in 1:100){ > model<-update(model,.~.+x[,i],singular.ok=T,na.action=na.omit)} If the above code is represented as below, I can get the correct result. However, I must use the loops. >model<-lm(y~x1,singular.ok=T,na.action=na.omit) >model<-u...

...15 9.00720e+15 -4.5036e+15 > [2,] 9.0072e+15 -1.80144e+16 9.0072e+15 > [3,] -4.5036e+15 9.00720e+15 -4.5036e+15 >> eigen(A) > $values > [1] 1.611684e+01 -1.116844e+00 -1.303678e-15 > > with a condition number of 1.236260e+16 I think I'd like it to tell me it's singular like it used to :) and I know it is singular Under 1.6.0 also on XP I get > solve(A,1:3) Error in solve.default(A, 1:3) : singular matrix `a' in solve > solve(A) Error in solve.default(A) : singular matrix `a' in solve > eigen(A) $values [1] 1.611684e+01 -1.116844e+00 -1.120...

..., I get the following error messages: [code]fixme:ntoskrnl:KeInitializeTimerEx stub: 0x110ff8 0 fixme:actctx:parse_depend_manifests Could not find dependent assembly L"Microsoft.VC90.CRT" (9.0.21022.8) err:module:import_dll Library d3dx10_42.dll (which is needed by L"D:\\Activision\\Singularity\\Binaries\\Singularity.exe") not found err:module:import_dll Library XAPOFX1_3.dll (which is needed by L"D:\\Activision\\Singularity\\Binaries\\Singularity.exe") not found err:module:import_dll Library MSVCP90.dll (which is needed by L"D:\\Activision\\Singularity\\Binaries\\S...

Dear R-listers, I have a dxr matrix Z, where d > r. And the product Z*Z' is a singular square matrix. The problem is how to get the left inverse U of this singular matrix Z*Z', such that U*(Z*Z') = I? Is there any to figure it out using matrix decomposition method? Thanks a lot for your help. Fred

Dear Terry, Even the behaviour of lm() and glm() isn't entirely consistent. In both cases, singularity results in NA coefficients by default, and these are reported in the model summary and coefficient vector, but not in the coefficient covariance matrix: ---------------- > mod.lm <- lm(Employed ~ GNP + Population + I(GNP + Population), + data=longley) > summary(mod.lm)...

Quantreggers: I'm trying to run rq() on a dataset I posted at: https://docs.google.com/file/d/0B8Kij67bij_ASUpfcmJ4LTFEUUk/edit?usp=sharing (it's a 1500kb csv file named "singular.csv") and am getting the following error: mydata <- read.csv("singular.csv") fit_spl <- rq(raw_data[,1] ~ bs(raw_data[,i],df=15),tau=1) > Error in rq.fit.br(x, y, tau = tau, ...) : Singular design matrix Any ideas what might be causing this or, more importantly, suggestion...

...c(15, 16, 17, 18, 19) # arbitrary example data here; y <- c(0.1, 1.8, 2.2, 2.6, 2.9) # actual data is similar gm <- nls(y ~ a+b*exp(-exp(-c*(x-d))), start=c(a=?, b=?, c=?, d=?)) I have been unable to properly set the starting value '?'s. All of my guesses yield either a "singular gradient" error if they are decent guesses, or a "singular gradient matrix at initial parameter estimates" error if they are bad guesses like all zeros. How can I pick starting values that don't result in singular gradients? I have had no luck with the "selfStart" mod...

Dear Users, I am a new user of the sem package. I have a model that is being flagged by sem as "S is numerically singular: expect problems" I have checked John Fox's response to a similar problem. Obviously the variance-covariance matrix is singular, but none of the possible reasons seems to hold in my case. Any leads how I could get the model to work? from Prof. John Fox That seems to me a reasonably inf...

...) \ && (umask 022 ; mkdir /var/dovecot/empty) \ && (umask 027 ; mkdir /var/dovecot/token-login) -----Original Message----- From: cesco [mailto:cesco at esiliati.org] Sent: 30 December 2019 18:32 To: dovecot at dovecot.org Subject: dovecot cannot drop privileges inside singularity container Hi all I'm facing an issue while running dovecot inside a singularity (https://sylabs.io/singularity/) container dovecot version is 2.3.4.1 (configuration below) running on debian buster, inside a container made with singularity version 3.4.2 unfortunately, when I try to start...