Dear Stefano,

You've already had a couple of informative responses directly addressing your 
question, but are you aware how ill-conditioned the matrix is (one of the 
responses alluded to this)?

> kappa(X, exact=TRUE)
[1] 7.313338e+12

> eigen(X)$values
[1] 4.964711e+00 9.356881e-01 4.863392e-12 6.788344e-13

Two of the variables have variances around 10^0 and the other two around 
10^-12. Of course, you haven't said anything about the context, but does it 
really make sense to analyze the data on these scales?

Best,
 John

-----------------------------
John Fox, Professor
McMaster University
Hamilton, Ontario
Canada L8S 4M4
Web: socserv.mcmaster.ca/jfox




> -----Original Message-----
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Stefano Sofia
> Sent: December 10, 2015 5:08 AM
> To: r-help@r-project.org
> Subject: [R] matrix which results singular but at the same time positive 
> definite
> 
> Dear list users,
> through the "matrixcalc" package I am performing some checks of variance
> matrices (which must be positive definite).
> In this example, it happens that the matrix A here reported is singular but
> positive definite. Is it possible?
> 
>               [,1]          [,2]          [,3]          [,4]
> [1,]  1.904255e-12 -1.904255e-12 -8.238960e-13 -1.240294e-12 [2,] -
> 1.904255e-12  3.637979e-12  1.364242e-12  1.818989e-12 [3,] -8.238960e-13
> 1.364242e-12  4.809988e+00  7.742369e-01 [4,] -1.240294e-12  1.818989e-12
> 7.742369e-01  1.090411e+00
> 
> print(is.non.singular.matrix(A, tol = 1e-18)) FALSE 
> print(is.positive.definite(A,
> tol=1e-18)) TRUE
> 
> Is there something wrong with this matrix?
> Any comment will be appreciated.
> Stefano
> 
> 
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