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Surfpack:
A Library of Multidimensional Surface Fitting Methods 

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Anthony A. Giunta
Mark Richards
Eric Cyr
Shannon L. Brown
Laura P. Swiler
Michael S. Eldred

Contact:
Anthony A. Giunta
Sandia National Laboratories
P.O. Box 5800, Mail Stop 0828
Albuquerque, NM 87185-0828
Email: surfpack@scico.sandia.gov
Web: http://endo.sandia.gov/Surfpack

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License:

Surfpack is distributed under the GNU General Public License. It is free
software; you can redistribute it and/or modify it under the terms of the GNU
General Public License as published by the Free Software Foundation; either
version 2 of the License, or (at your option) any later version.  A copy of
this license is included in the GNU_LICENSE_INFO file, and is also available
online from http://www.gnu.org/copyleft/gpl.html.  Also refer to the COPYRIGHT
file for important U.S. Government legal notices.

The Surfpack distribution contains libraries which are available separately
under compatible licensing terms.  In particular, many of the libraries in src
are available separately under either the GNU Lesser General Public License
(LGPL) or General Public License (GPL).

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Overview:

The Surfpack library provides a collection of surface fitting methods and
quality-of-fit metrics that can be used to quantify the error in the resulting
approximations.  Currently supported data-fitting algorithms include
least-squares linear regression, multivariate adaptive regression splines
(MARS), Kriging interpolation, artificial neural networks, and radial basis
function networks.  These algorithms are available both as a C++ library and as
a standalone program with a simple shell interface.

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Surfpack References:

General Information on Surfpack
Web: http://endo.sandia.gov/Surfpack
Surfpack User's Manual (available on the website)


Technical Documents:

Giunta, A. A., Swiler, L. P., Brown, S. L., Eldred, M. S., Richards, M. D., 
and Cyr, E. C., "The Surfpack Software Library for Surrogate Modeling of 
Sparse Irregularly Spaced Multidimensional Data," (to appear) 11th AIAA/ISSMO
Multidisciplinary Analysis and Optimization Conference, AIAA Paper 2006-XXXX,
Portsmouth, VA, 2006.


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