Meta modeling

General purpose metamodels

Create a linear least squares model

Create a general linear model metamodel

Taylor approximations

Create a linear model

Mixture of experts

Perfom stepwise regression

Over-fitting and model selection

Polynomial chaos metamodel

Apply a transform or inverse transform on your polynomial chaos

Fit a distribution from an input sample

Polynomial chaos exploitation

Polynomial chaos over database

Compute grouped indices for the Ishigami function

Validate a polynomial chaos

Polynomial chaos graphs

Create a polynomial chaos metamodel by integration on the cantilever beam

Advanced polynomial chaos construction

Create a polynomial chaos metamodel

Create a polynomial chaos for the Ishigami function: a quick start guide to polynomial chaos

Polynomial chaos is sensitive to the degree

Create a sparse chaos by integration

Kriging metamodel

Kriging : propagate uncertainties

Kriging : multiple input dimensions

Kriging : draw the likelihood

Kriging : cantilever beam model

Configuring an arbitrary trend in Kriging

Kriging the cantilever beam model using HMAT

Kriging : generate trajectories from a metamodel

Choose the trend basis of a kriging metamodel

Kriging with an isotropic covariance function

Kriging: metamodel of the Branin-Hoo function

Kriging : quick-start

Sequentially adding new points to a kriging

Advanced kriging

Kriging :configure the optimization solver

Kriging : choose a trend vector space

Kriging : draw covariance models

Low rank tensors metamodel

Tensor approximation of the cantilever beam model

Fields metamodels

Validation of a Karhunen-Loeve decomposition

Viscous free fall: metamodel of a field function

Metamodel of a field function