Meta modelling

General classes

MetaModelAlgorithm(*args)	Base class for metamodel algorithms.
MetaModelResult(*args)	Data structure containing a metamodel.
MetaModelValidation(*args)	Scores a metamodel in order to perform its validation.

Parametric

Taylor approximation

Refer to Taylor expansion.

LinearTaylor(*args)	First order polynomial response surface by Taylor expansion.
QuadraticTaylor(*args)	Second-order Taylor expansion.

Least squares approximation

LinearLeastSquares(*args)	First order polynomial response surface by least squares.
QuadraticLeastSquares(*args)	Second order polynomial response surface by least squares.

Linear model algorithm

Main classes

LinearModelAlgorithm(*args)	Class used to create a linear regression model.
LinearModelResult(*args)	Result of a LinearModelAlgorithm.
LinearModelStepwiseAlgorithm(*args)	Stepwise linear model algorithm.

Post-processing

LinearModelAnalysis(*args)	Analyse a linear model.
experimental.LinearModelValidation(*args)	Validate a linear regression metamodel.

Generalized Linear Model algorithm

GeneralLinearModelAlgorithm(*args)	Algorithm for the evaluation of general linear models.
GeneralLinearModelResult(*args)	General linear model result.

Gaussian Process Regression

Main classes

experimental.GaussianProcessRegression(*args)	Gaussian process regression algorithm.
experimental.GaussianProcessFitter(*args)	Fit gaussian process models
experimental.GaussianProcessRegressionResult(*args)	Gaussian process regression (aka kriging) result.
experimental.GaussianProcessFitterResult(*args)	Gaussian process fitter result.
experimental.GaussianProcessConditionalCovariance(*args)	Conditional covariance post processing of a Gaussian Process Regression result.
experimental.GaussianProcessRandomVector(*args)	GaussianProcessRandom vector, a conditioned Gaussian process.

Construction of the regression basis

BasisFactory(*args)	Basis factory base class.
ConstantBasisFactory(*args)	Constant basis factory.
LinearBasisFactory(*args)	Linear basis factory.
QuadraticBasisFactory(*args)	Quadratic basis factory.

Functional chaos expansion

Main classes

FunctionalChaosAlgorithm(*args)	Functional chaos algorithm.
LeastSquaresExpansion(*args)	L2 approximation on an orthonormal basis using least-squares and a fixed basis.
IntegrationExpansion(*args)	L2 approximation on an orthonormal basis using least-squares and a fixed basis.

Construction of the truncated multivariate orthogonal basis

AdaptiveStrategy(*args)	Base class for the construction of the truncated multivariate orthogonal basis.
CleaningStrategy(*args)	Cleaning truncation strategy.
FixedStrategy(*args)	Fixed truncation strategy.

Projection method

ProjectionStrategy(*args)	Base class for the evaluation strategies of the approximation coefficients.
IntegrationStrategy(*args)	Integration strategy for the approximation coefficients.
LeastSquaresStrategy(*args)	Least squares strategy for the approximation coefficients.

Least squares algorithms to compute the coefficients

ApproximationAlgorithm(*args)	Approximation algorithm.
ApproximationAlgorithmImplementationFactory(*args)	Approximation algorithm factory base class.
PenalizedLeastSquaresAlgorithmFactory(*args)	Penalized least squares algorithm factory.
PenalizedLeastSquaresAlgorithm(*args)	Penalized least squares algorithm.
LeastSquaresMetaModelSelectionFactory(*args)	Least squares metamodel selection factory.
LeastSquaresMetaModelSelection(*args)	Least squares metamodel selection factory.

Model selection algorithm

BasisSequenceFactory(*args)	Basis sequence factory.
LARS(*args)	Least Angle Regression.

Model selection criteria

FittingAlgorithm(*args)	Fitting algorithm.
CorrectedLeaveOneOut(*args)	Corrected leave one out.
KFold(*args)	K-fold.

Least Squares problem resolution

Refer to Least squares problems numerical methods.

LeastSquaresMethod(*args)	Base class for least square solvers.
CholeskyMethod(*args)	Least squares solver using Cholesky decomposition.
SVDMethod(*args)	Least squares solver using SVD decomposition.
QRMethod(*args)	Least squares solver using the QR decomposition.
SparseMethod(*args)	Least squares solver using a sparse representation.
DesignProxy(*args)	Design matrix cache.

Results

FunctionalChaosRandomVector(*args)	Functional chaos random vector.
FunctionalChaosResult(*args)	Functional chaos result.
FunctionalChaosSobolIndices(*args)	Sensitivity analysis based on functional chaos expansion.
experimental.FunctionalChaosValidation(*args)	Validate a functional chaos metamodel.

Functional chaos on fields

FieldToPointFunctionalChaosAlgorithm(*args)	Functional metamodel algorithm based on chaos decomposition.
FieldFunctionalChaosResult(*args)	Functional metamodel result.
FieldFunctionalChaosSobolIndices(*args)	Sobol indices from a functional decomposition.
experimental.PointToFieldFunctionalChaosAlgorithm(*args)	Functional metamodel algorithm based on chaos decomposition.