Hi Ben and JS,
Thanks for the reply.
I tried using: hessian(func = h_x, x, method = "complex"), it gives zero,
that's good.
# R code
> hess.h <- hessian(func = h_x, x, method = "complex")
> mat <- h_x(x)*hess.h - grad(h_x, x) %o% grad(h_x, x)
> mat
[,1] [,2] [,3] [,4]
[1,] 2060602 0 0 0
[2,] 0 2060602 0 0
[3,] 0 0 -4039596 -816080
[4,] 0 0 -816080 4039596
But later I do,
> eigen(mat)
$values
[1] -4121204 4121204 2060602 2060602
$vectors
[,1] [,2] [,3] [,4]
[1,] 0.00000000 0.00000000 1 0
[2,] 0.00000000 0.00000000 0 1
[3,] -0.99503719 0.09950372 0 0
[4,] -0.09950372 -0.99503719 0 0
And here is the problem,
> eigen(mat)$values[2] == 4121204
[1] FALSE
> eigen(mat)$values[2] - 4121204
[1] -5.494803e-08
Why doesn't the second value equal to 412104? How do I overcome that?
Thanks,
Mike
On Wed, Feb 18, 2015 at 9:13 AM, JS Huang <js.hu...@protective.com> wrote:
> Hi,
>
> Since all entries in your hessian matrix and grad vector are integers, I
> suggest you execute the following for mat assignment.
>
> > mat <- round(h_x(x),digits=0)*round(hess.h,digits=0) - round(grad(h_x,
> > x),digits=0) %o% round(grad(h_x, x),digits=0)
> > mat
> [,1] [,2] [,3] [,4]
> [1,] 0 0 0 -4080400
> [2,] 0 7920000 0 -1600000
> [3,] 0 0 12160400 0
> [4,] -4080400 -1600000 0 -7920000
>
>
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/Numerical-stability-of-eigenvalue-and-hessian-matrix-in-R-tp4703443p4703456.html
> Sent from the R help mailing list archive at Nabble.com.
>
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