[R] matrix which results singular but at the same time positive definite

Stefano Sofia stefano.sofia at regione.marche.it
Thu Dec 10 16:41:52 CET 2015


Dear John,
thank you for your considerations.
This matrix (which is a variance matrix) is part of an algorithm for forward-filtering and backward-sampling of Dynamic Linear Models (West and Harrison, 1997), applied to DLM representation of ARIMA processes (Petris, Petrone, Campagnoli).  It is therefore very difficult to explain why this variance matrix becomes so ill conditioned. This already happens at the first iteration of the algorithm. I will try to work on initial conditions and some fixed parameters.

Thank you again
Stefano


________________________________________
Da: Fox, John [jfox at mcmaster.ca]
Inviato: giovedì 10 dicembre 2015 14.41
A: Stefano Sofia; r-help at r-project.org
Oggetto: RE: matrix which results singular but at the same time positive        definite

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-bounces at r-project.org] On Behalf Of Stefano Sofia
> Sent: December 10, 2015 5:08 AM
> To: r-help at 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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