We propose a thorough comparison of polynomial chaos expansion (PCE) for indicator functions of the form 1 c≤X for some threshold parameter c ∈ R and a random variable X associated with classical orthogonal polynomials. We provide tight global and localized L2 estimates for the resulting truncation of the PCE and numerical experiments support the tightness of the error estimates. We also compare the theoretical and numerical accuracy of PCE when extra quantile/probability transforms are applied, revealing different optimal choices according to the value of c in the center and the tails of the distribution of X
In the field of computer experiments sensitivity analysis aims at quantifying the relative importanc...
Abstract. Recently, the use of Polynomial Chaos Expansion (PCE) has been in-creasing to study the un...
This paper deals with the analysis of the dynamic behavior of nonlinear systems subject to probabili...
We propose a thorough comparison of polynomial chaos expansion (PCE) for indicator functions of the ...
Polynomial Chaos Expansions (PCEs) offer an efficient alternative to assess the statistical properti...
A number of approaches for discretizing partial differential equations with random data ar...
Polynomial chaos expansions (PCE) are an attractive technique for uncertainty quan-tification (UQ) d...
Recently, the use of Polynomial Chaos Expansion (PCE) has been increasing to study the uncertainty i...
Abstract. In this paper we review some applications of generalized polynomial chaos expansion for un...
Inherent physical uncertainties can have a significant influence on computational predictions. It is...
Uncertainty quantification seeks to provide a quantitative means to understand complex systems that ...
The generalized Polynomial Chaos Expansion Method (gPCEM), which is a random uncertainty analysis me...
Polynomial chaos (PC) expansions are used for the propagation of uncertainty through dynamical syste...
This paper investigates the fundamental nature of the polynomial chaos (PC) response of dynamic syst...
International audienceA methodology and algorithms are proposed for constructing the polynomial chao...
In the field of computer experiments sensitivity analysis aims at quantifying the relative importanc...
Abstract. Recently, the use of Polynomial Chaos Expansion (PCE) has been in-creasing to study the un...
This paper deals with the analysis of the dynamic behavior of nonlinear systems subject to probabili...
We propose a thorough comparison of polynomial chaos expansion (PCE) for indicator functions of the ...
Polynomial Chaos Expansions (PCEs) offer an efficient alternative to assess the statistical properti...
A number of approaches for discretizing partial differential equations with random data ar...
Polynomial chaos expansions (PCE) are an attractive technique for uncertainty quan-tification (UQ) d...
Recently, the use of Polynomial Chaos Expansion (PCE) has been increasing to study the uncertainty i...
Abstract. In this paper we review some applications of generalized polynomial chaos expansion for un...
Inherent physical uncertainties can have a significant influence on computational predictions. It is...
Uncertainty quantification seeks to provide a quantitative means to understand complex systems that ...
The generalized Polynomial Chaos Expansion Method (gPCEM), which is a random uncertainty analysis me...
Polynomial chaos (PC) expansions are used for the propagation of uncertainty through dynamical syste...
This paper investigates the fundamental nature of the polynomial chaos (PC) response of dynamic syst...
International audienceA methodology and algorithms are proposed for constructing the polynomial chao...
In the field of computer experiments sensitivity analysis aims at quantifying the relative importanc...
Abstract. Recently, the use of Polynomial Chaos Expansion (PCE) has been in-creasing to study the un...
This paper deals with the analysis of the dynamic behavior of nonlinear systems subject to probabili...