Some new error estimates for statistical estimators obtained by Neumann-Monte Carlo methodology applied to the stochastic bending problem

DOI10.1080/03610918.2020.1827267OpenAlexW3092105599MaRDI QIDQ5055183

Roberto M. F. Squarcio, Claudio R. S. Jun. Ávila

Publication date: 13 December 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2020.1827267

zbMATH Keywords

Galerkin methoderror estimatesMonte Carlo simulationNeumann seriesquantification of uncertaintystochastic bending

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Sparse high order FEM for elliptic sPDEs
• Analysis of a curved beam on uncertain elastic foundation.
• An efficient 3D stochastic finite element method
• On solving elliptic stochastic partial differential equations
• A stochastic finite element dynamic analysis of structures with uncertain parameters
• Explicit solution to the stochastic system of linear algebraic equations \((\alpha _{1}\boldsymbol{A}_{1} + \alpha _{2}\boldsymbol{A}_{2} +\cdots+ \alpha _{m}\boldsymbol{A}_{m})\boldsymbol{x} = \boldsymbol{b}\)
• Stochastic finite element simulation of random structure on uncertain foundation under random loading
• On stochastic finite elements for structural analysis
• Galerkin Finite Element Approximations of Stochastic Elliptic Partial Differential Equations

This page was built for publication: Some new error estimates for statistical estimators obtained by Neumann-Monte Carlo methodology applied to the stochastic bending problem