.. _meta_modeling:

Meta modeling
=============

The current section is dedicated to the building of an analytical approximation of the model of a given model.
Such an approximation is commonly referred to as a response surface in the literature.
This methodology is relevant if each model evaluation is time consuming.
Indeed, once a surrogate model has been built up, the various propagation steps may be applied at a negligible cost.

Local approximation
-------------------

.. toctree::
    :maxdepth: 1

    taylor_expansion


Least squares surrogate models
------------------------------

.. toctree::
    :maxdepth: 1

    least_squares
    sparse_least_squares


Gaussian Process Regression
---------------------------

.. toctree::
    :maxdepth: 1

    gaussian_process_regression


Functional chaos
----------------

.. toctree::
    :maxdepth: 1

    functional_chaos
    chaos_basis
    orthonormal_polynomials
    enumeration_multivariate_basis


Surrogate validation
--------------------

.. toctree::
    :maxdepth: 1

    cross_validation
