The usual identification methods of polynomial chaos expansions in high dimension are based on the use of a series of truncations that induce numerical bias. We first quantify the detrimental influence of this numerical bias, we then propose a new decomposition of the polynomial chaos coefficients to allow performing relevant convergence analysis and identification with respect to an arbitrary measure for the high dimension case.
Identification of polynomial chaos representations in high dimension