bayesvalidrox.surrogate_models.eval_rec_rule

Based on the implementation in UQLab [1].

References: 1. S. Marelli, and B. Sudret, UQLab: A framework for uncertainty quantification in Matlab, Proc. 2nd Int. Conf. on Vulnerability, Risk Analysis and Management (ICVRAM2014), Liverpool, United Kingdom, 2014, 2554-2563.

2. S. Marelli, N. Lüthen, B. Sudret, UQLab user manual – Polynomial chaos expansions, Report # UQLab-V1.4-104, Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, Switzerland, 2021.

Author: Farid Mohammadi, M.Sc. E-Mail: farid.mohammadi@iws.uni-stuttgart.de Department of Hydromechanics and Modelling of Hydrosystems (LH2) Institute for Modelling Hydraulic and Environmental Systems (IWS), University of Stuttgart, www.iws.uni-stuttgart.de/lh2/ Pfaffenwaldring 61 70569 Stuttgart

Created on Fri Jan 14 2022

Functions

eval_rec_rule(x, max_deg, poly_type)	Evaluates the polynomial that corresponds to the Jacobi matrix defined from the AB.
eval_rec_rule_arbitrary(x, max_deg, poly_coeffs)	Evaluates the polynomial at sample array x.
eval_univ_basis(x, max_deg, poly_types[, ...])	Evaluates univariate regressors along input directions.
poly_rec_coeffs(n_max, poly_type[, params])	Computes the recurrence coefficients for classical Wiener-Askey orthogonal polynomials.