A numerical method for solving linear systems in the preconditioned Crank-Nicolson algorithm

DOI10.1016/j.aml.2020.106254zbMath1503.65019OpenAlexW3003375242MaRDI QIDQ2176488

Elias D. Nino Ruiz

Publication date: 4 May 2020

Published in: Applied Mathematics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.aml.2020.106254

zbMATH Keywords

Markov chain Monte Carloiterative solutionpreconditioned Crank-Nicolson algorithm

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Stability and convergence of numerical methods for ordinary differential equations (65L20) Numerical solutions to stochastic differential and integral equations (65C30) Finite difference and finite volume methods for ordinary differential equations (65L12)

Uses Software

• CODA
• MCMCglmm

Cites Work

• A new proof of convergence of MCMC via the ergodic theorem
• A derivative-free trust region framework for variational data assimilation
• Covariance regularization by thresholding
• Local search methods for the solution of implicit inverse problems
• Nonlinear data assimilation
• Testing for chaos in deterministic systems with noise
• MCMC methods for functions: modifying old algorithms to make them faster

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