This is an implemenatation of three polynomial basis surrogate models, namely:
-
full polynomial chaos expansions
-
sparse polynomials chaos expansions according to
Blatman, G. and B. Sudret (2011). Adaptive sparse polynomial chaos expansion based on least-angle regression. Journal of Computational Physics 230(6), 2345 - 2367.
- continuous-space low-rank approximations in canonical polyadics format according to
Konakli, K. and B. Sudret (2016b). Polynomial meta-models with canonical low-rank approximations: Numerical insights and comparison to sparse polynomial chaos expansions. Journal of Computational Physics 321, 1144 - 1169.
Includes Variance-based sensitivity analysis for
- full and sparse PCE-based according to
Sudret, B. (2008). Global sensitivity analysis using polynomial chaos expansions. Reliability Engineering And System Safety 93(7), 964 - 979.
- (not yet) LRA-based variance-based sensitivity indices according to
Konakli, K. and B. Sudret (2016). Global sensitivity analysis using low-rank tensor approximations. Reliability Engineering & System Safety 156 (Supplement C), 64 - 83.