bayesvalidrox.surrogate_models.apoly_construction.apoly_construction

bayesvalidrox.surrogate_models.apoly_construction.apoly_construction(Data, degree)

Construction of Data-driven Orthonormal Polynomial Basis Author: Dr.-Ing. habil. Sergey Oladyshkin Department of Stochastic Simulation and Safety Research for Hydrosystems Institute for Modelling Hydraulic and Environmental Systems Universitaet Stuttgart, Pfaffenwaldring 5a, 70569 Stuttgart E-mail: Sergey.Oladyshkin@iws.uni-stuttgart.de http://www.iws-ls3.uni-stuttgart.de The current script is based on definition of arbitrary polynomial chaos expansion (aPC), which is presented in the following manuscript: Oladyshkin, S. and W. Nowak. Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion. Reliability Engineering & System Safety, Elsevier, V. 106, P. 179-190, 2012. DOI: 10.1016/j.ress.2012.05.002.

Parameters

Dataarray

Raw data.

degreeint

Maximum polynomial degree.

Returns

Polynomialarray

The coefficients of the univariate orthonormal polynomials.