SPARSE_GRID_HERMITE
Sparse Grids Based on Gauss-Hermite Rules


SPARSE_GRID_HERMITE is a MATLAB library which constructs sparse grids based on 1D Gauss-Hermite rules.

Sparse grids are more naturally constructed from a nested family of quadrature rules. Gauss-Hermite rules are not nested, but have higher accuracy. Thus, there can be a tradeoff. If we compare two sparse grids of the same "level", one using Gauss-Hermite rules and the other a nested rule, then the Gauss-Hermite sparse grid will have higher accuracy...but also a significantly greater number of points. When measuring efficiency, we really need to balance the cost in quadrature points against the accuracy, and so it is not immediately obvious which choice is best!

To slightly complicate matters, Gauss-Hermite rules are very weakly nested, in that the rules of odd order all include the abscissa value X=0.0. A sparse grid constructed from Gauss-Hermite rules will thus have to keep track of this minor point as well.

Here is a table showing the number of points in a sparse grid based on Gauss-Hermite rules, indexed by the spatial dimension, and by the "level", which is simply an index for the family of sparse grids.
DIM:123456
LEVEL_MAX      
0111111
135791113
2722375781109
31575161289471713
431224608126823413953
563613207049941036719397
612715706507180764195786522

Licensing:

The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.

Related Data and Programs:

CC_DISPLAY is a MATLAB library which can compute and display Clenshaw Curtis grids in two dimensions, as well as sparse grids formed from sums of Clenshaw Curtis grids.

CLENSHAW_CURTIS is a MATLAB library which can compute Clenshaw Curtis grids in multiple dimensions, as well as sparse grids formed from sums of Clenshaw Curtis grids.

QUADRATURE_RULES is a dataset directory of files which define quadrature rules; a number of examples of sparse grid quadrature rules are included.

QUADRULE is a MATLAB library which defines quadrature rules for various intervals and weight functions.

SGMGA, a MATLAB library which creates sparse grids based on a mixture of 1D quadrature rules, allowing anisotropic weights for each dimension.

SMOLPACK is a C library which implements Novak and Ritter's method for estimating the integral of a function over a multidimensional hypercube using sparse grids.

SPARSE_GRID_CC is a MATLAB library which computes sparse grids based on a Clenshaw-Curtis rule.

SPARSE_GRID_CLOSED is a MATLAB library which defines sparse grids based on closed nested quadrature rules.

SPARSE_GRID_COMPOSITE, a MATLAB library which creates sparse grids based on 1D composite rules (currently only of order 1).

SPARSE_GRID_DISPLAY is a MATLAB library which can display a 2D or 3D sparse grid.

SPARSE_GRID_F2 is a dataset directory of sparse grids based on a Fejer Type 2 rule.

SPARSE_GRID_GL is a MATLAB library which computes a sparse grid based on 1D Gauss-Legendre rules.

SPARSE_GRID_GP is a dataset directory of sparse grids based on a Gauss Patterson rule.

SPARSE_GRID_HERMITE is available in a C++ version and a FORTRAN90 version and a MATLAB version.

SPARSE_GRID_HERMITE is a dataset directory which contains sparse grids based on a Gauss-Hermite rule.

SPARSE_GRID_MIXED is a MATLAB library which constructs a sparse grid using different rules in each spatial dimension.

SPARSE_GRID_NCC is a dataset directory which contains sparse grids based on a Newton Cotes closed rule.

SPARSE_GRID_NCO is a dataset directory which contains sparse grids based on a Newton Cotes open rule.

SPARSE_GRID_OPEN is a MATLAB library which defines sparse grids based on open nested quadrature rules.

TOMS847 is a MATLAB program which uses sparse grids to carry out multilinear hierarchical interpolation. It is commonly known as SPINTERP, and is by Andreas Klimke.

Reference:

  1. Volker Barthelmann, Erich Novak, Klaus Ritter,
    High Dimensional Polynomial Interpolation on Sparse Grids,
    Advances in Computational Mathematics,
    Volume 12, Number 4, 2000, pages 273-288.
  2. Thomas Gerstner, Michael Griebel,
    Numerical Integration Using Sparse Grids,
    Numerical Algorithms,
    Volume 18, Number 3-4, 1998, pages 209-232.
  3. Albert Nijenhuis, Herbert Wilf,
    Combinatorial Algorithms for Computers and Calculators,
    Second Edition,
    Academic Press, 1978,
    ISBN: 0-12-519260-6,
    LC: QA164.N54.
  4. Fabio Nobile, Raul Tempone, Clayton Webster,
    A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data,
    SIAM Journal on Numerical Analysis,
    Volume 46, Number 5, 2008, pages 2309-2345.
  5. Sergey Smolyak,
    Quadrature and Interpolation Formulas for Tensor Products of Certain Classes of Functions,
    Doklady Akademii Nauk SSSR,
    Volume 4, 1963, pages 240-243.
  6. Dennis Stanton, Dennis White,
    Constructive Combinatorics,
    Springer, 1986,
    ISBN: 0387963472,
    LC: QA164.S79.

Tar File:

A GZIP'ed TAR file of the contents of this directory is available.

Source Code:

Examples and Tests:

You can go up one level to the MATLAB source codes.


Last revised on 08 October 2007.