> Date: Tue, 16 Nov 2010 17:39:57 -0800
> From: peter.langfel...@gmail.com
> To: jbass...@cs.gmu.edu
> CC: r-help@r-project.org
> Subject: Re: [R] Non-positive definite cross-covariance matrices
>
> > Peter,
> >
>
> Peter,
>
> I see your point. As it turns out though, what I'm trying to
> calculate is heritability using a slightly modified version of an
> equation from multivariate quantitative genetics. Theoretically I
> suppose a heritability matrix could be non-positive definite, but in
> practice it al
On Tue, Nov 16, 2010 at 1:49 PM, Peter Langfelder
wrote:
>
> It is easy to come up with examples where Cov(A, B) + Cov(B, A) is not
> positive definite. As an extreme example, consider a matrix A (say 10
> columns, 100 rows) such that the off-diagonal covariances are all zero
> and the columns are
On Tue, Nov 16, 2010 at 9:40 AM, Jeff Bassett wrote:
> Giovanni,
>
> Both matrices describing the points (A and B in my example) are the
> same size, so the resulting matrix will always be square. Also, the
> equation I'm using is essentially the following identity:
>
> Var(A + B) = Var(A) + Var(
Giovanni,
Both matrices describing the points (A and B in my example) are the
same size, so the resulting matrix will always be square. Also, the
equation I'm using is essentially the following identity:
Var(A + B) = Var(A) + Var(B) + Cov(A, B) + Cov(B, A)
All the covariance matrices that resul
What made you think that a cross-covariance matrix should be positive
definite? Id does not even need to be a square matrix, or symmetric.
Giovanni Petris
On Mon, 2010-11-15 at 12:58 -0500, Jeff Bassett wrote:
> I am creating covariance matrices from sets of points, and I am having
> frequent pro
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