Displaying 20 results from an estimated 10000 matches similar to: "Kriging"
2012 Oct 25
5
system is computationally singular: reciprocal condition number
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
2005 May 03
1
multivariate Shapiro Wilks test
Hello,
I have a question about multivariate Shapiro-Wilks test.
I tried to analyze if the data I have are multivariate normal, or how
far they are from being
multivariate normal. However, any time I did
>mshapiro.test(mydata)
I get the message:
Error in solve.default(R %*% t(R), tol = 1e-18) :
system is computationally singular: reciprocal condition number
= 5.38814e-021
I tried
2007 Jul 26
1
zeroinfl() or zicounts() error
I'm trying to fit a zero-inflated poisson model using zeroinfl() from the
pscl library. It works fine for most models I try, but when I include either
of 2 covariates, I get an error.
When I include "PopulationDensity", I get this error: Error in solve.default
(as.matrix(fit$hessian)) : system is computationally singular:
reciprocal condition number = 1.91306e-34
When I
2012 Dec 11
2
Catching errors from solve() with near-singular matrices
Dear all,
The background is that I'm trying to fix this bug in the geometry
package:
https://r-forge.r-project.org/tracker/index.php?func=detail&aid=1993&group_id=1149&atid=4552
Boiled down, the problem is that there exists at least one matrix X for
which det(X) != 0 and for which solve(X) fails giving the error "system
is computationally singular: reciprocal condition
2006 Nov 07
4
solve computationally singular
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;
2006 Jan 10
1
glmmPQL / "system is computationally singular"
Hi,
I'm having trouble with glmmPQL from the MASS package.
I'm trying to fit a model with a binary response variable, two fixed
and two random variables (nested), with a sample of about 200,000
data points.
Unfortunately, I'm getting an error message that is difficult to
understand without knowing the internals of the glmmPQL function.
> model <- glmmPQL(primed ~
2011 Mar 16
2
Singularity problem
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
Thanks in advance!
Feng
--
2004 Dec 09
1
System is computationally singular?
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
2007 Dec 12
2
Matrix Inversion
I got the following error:
a = read.csv("mat.csv")
b = as.matrix(a)
tb = t(b)
bb = tb %*% b
dim(bb)
ibb = solve(bb)
bb %*% ibb
> ibb = solve(bb)
Error in solve.default(bb) :
system is computationally singular: reciprocal condition number =
1.77573e-19
>
Are there any ways to find more information about why it is singular?
Thanks.
2024 Apr 23
0
System GMM fails due to computationally singular system. Why?
A copy of this question can be found on Cross Validated:
https://stats.stackexchange.com/questions/645610
I am estimating a system of seemingly unrelated regressions (SUR) with
`gmm::sysGmm` in R. Each of the equations has one unique regressor and one
common regressor. The common regressor is a dummy variable indicating the
last observation (n-1 zeros followed by 1). I impose a restriction that
2009 Nov 18
2
Error "system is computationally singular" by using function dmvnorm
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?
2006 Sep 06
1
singular factor analysis
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,
2008 Oct 06
0
Computationally singular [provides coefficients but not covariance matrix]
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,
2007 Jun 01
1
Determinant function (PR#9715)
Full_Name: Krzysztof Podgorski
Version: R version 2.4.1 (2006-12-18)
OS: Windows XP
Submission from: (NULL) (130.235.3.79)
The function ''det'' works improperly for a singular matrix and returns a
non-zero value even if ''solve'' reports singularity. The matrix is very simple
as shown below.
A <- diag(rep(c(64,8), c(8,8)))
A[9:16,1] <- 8
A[1,9:16] <- 8
2009 May 01
1
computationally singular and lack of variance parameters in SEM
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,
2013 Jan 13
1
R error: system is computationally singular when building GMM model
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,
2008 Feb 19
1
Matrix inversion
Howdy,
I am trying to invert a matrix for the purposes of least squares. I
have tried a number of things, and the variety of results has me
confused.
1. When I try solve() I get the following:
>Error in solve.default(t(X) %*% X) : system is computationally
singular: reciprocal condition number = 3.76391e-20
2. When I try qr.solve(), I get:
>Error in qr.solve(t(X) %*% X) : singular matrix
2010 Jul 19
1
Calculation of Covariance Matrix Calculation
Hi,
Excuse me for asking this silly question. But I really couldn't understand
why cov() and ccov() don't work for my calculation of covariance matrix.
a <- matrix(1:8, 2, 4)
a
[,1] [,2] [,3] [,4]
[1,] 1 3 5 7
[2,] 2 4 6 8
> ccov(a)
Error in solve.default(cov, ...) :
Lapack routine dgesv: system is exactly singular
I also tried colume bind, but it
2007 Oct 06
2
factanal: error message
Hi everyone,
I'm running a factor analysis on a correlation matrix with 32 rows and
columns.
I get the following error when I issue the command sequence
mich.fac1 <- factanal(michcor, factor=1)
Error in solve.default(cv) : system is computationally singular: reciprocal
condition number = 3.24729e-18
I'd really appreciate an explanation for this error and a solution to the
problem
2010 Aug 19
0
2d kriging with anisotropy on an irregular network (RandomFields Package)
Dear List
I am using the RandomFields package, and I have a problem when 2d-kriging, with an anisotropy, some values from an irregular network.
It works well when :
- 2d-kriging, without any anisotropy, some data from an irregular network
- 2d-kriging, with and without anisotropy, some data from a regular network
- 3d-kriging, with and without anisotropy, some data from a regular network
Here is