Adrian
It is a common misconception that using the covariance (total sill -
semi-variogram) rather than the semi-variogram brings more robust solutions.
You get exactly the same answer either way since one is just a constant minus
the other.
You can avoid solution problems by simple pivoting or by putting the
condition equation first -- sum of weights equals 1.
If you look at the details of the solution, you generally only have to pivot
the first equation to remove the diagonal zeroes.
Isobel
http://courses.kriging.com
Adrian Martínez Vargas <[EMAIL PROTECTED]> wrote:
What about to produce pseudo covariance to replace kriging matrix
in term of variogram to make more efficient the numerical solution of the
system? The ceros in the matrix diagonal are a problem in robustness and
efficiency!
Some one knows how to implement something like that? Papers/books can be
useful!
----- Original Message -----
From: Adrian Martínez Vargas
To: ai-geostats@jrc.it
Sent: Friday, March 28, 2008 5:23 PM
Subject: Numerical method to solve kriging equations
Hello dear list
What numerical method give faster and robust solution to kriging equations.
What to us as C++ library (for example TNT and JAMA?). It is usual to use
cholesky in the case of simple kriging.
I will appreciate your advice and experiences.
Best regards
Dr. Adrian Martínez Vargas
Revista Minería y Geología
ISMM, Las Coloradas, s/n
Moa, Holguín,
Cuba
CP. 83329
http://www.ismm.edu.cu/revistamg/index.htm
