Meta modeling¶
General purpose metamodels¶
Polynomial chaos metamodel¶
![](../_images/sphx_glr_plot_chaos_distribution_transformation_thumb.png)
Apply a transform or inverse transform on your polynomial chaos
Apply a transform or inverse transform on your polynomial chaos
![](../_images/sphx_glr_plot_functional_chaos_database_thumb.png)
Create a full or sparse polynomial chaos expansion
Create a full or sparse polynomial chaos expansion
![](../_images/sphx_glr_plot_chaos_cantilever_beam_integration_thumb.png)
Create a polynomial chaos metamodel by integration on the cantilever beam
Create a polynomial chaos metamodel by integration on the cantilever beam
![](../_images/sphx_glr_plot_functional_chaos_thumb.png)
Create a polynomial chaos metamodel from a data set
Create a polynomial chaos metamodel from a data set
![](../_images/sphx_glr_plot_chaos_ishigami_thumb.png)
Create a polynomial chaos for the Ishigami function: a quick start guide to polynomial chaos
Create a polynomial chaos for the Ishigami function: a quick start guide to polynomial chaos
Kriging metamodel¶
![](../_images/sphx_glr_plot_kriging_multioutput_firesatellite_thumb.png)
Example of multi output Kriging on the fire satellite model
Example of multi output Kriging on the fire satellite model
![](../_images/sphx_glr_plot_kriging_beam_trend_thumb.png)
Kriging: choose a polynomial trend on the beam model
Kriging: choose a polynomial trend on the beam model
![](../_images/sphx_glr_plot_kriging_categorical_thumb.png)
Kriging: metamodel with continuous and categorical variables
Kriging: metamodel with continuous and categorical variables