Variance reduction for additive functionals of Markov chains via martingale representations
From MaRDI portal
Publication:2114045
DOI10.1007/s11222-021-10073-zzbMath1482.62003arXiv1903.07373OpenAlexW4210453183MaRDI QIDQ2114045
Denis Belomestny, Eric Moulines, S. P. Samsonov
Publication date: 14 March 2022
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1903.07373
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Zero variance Markov chain Monte Carlo for Bayesian estimators
- Recursive computation of the invariant distribution of a diffusion
- Asymptotic behaviour of the stochastic Lotka-Volterra model.
- Weighted multilevel Langevin simulation of invariant measures
- Variance reduction for discretised diffusions via regression
- A distribution-free theory of nonparametric regression
- Rates of convergence of the Hastings and Metropolis algorithms
- Monte Carlo complexity of parametric integration
- Variance reduction for Markov chains with application to MCMC
- Dynamic analysis of stochastic Lotka-Volterra predator-prey model with discrete delays and feedback control
- An adaptive scheme for the approximation of dissipative systems
- Nonasymptotic convergence analysis for the unadjusted Langevin algorithm
- Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise.
- Concentration Inequalities
- Simulation and the Monte Carlo Method
- Markov Chains
- Control Variates for Estimation Based on Reversible Markov Chain Monte Carlo Samplers
- Adaptive simulation using perfect control variates
- A Multivariate Faa di Bruno Formula with Applications
- Monte Carlo Methods for Applied Scientists
- Theoretical Guarantees for Approximate Sampling from Smooth and Log-Concave Densities
- Control Functionals for Monte Carlo Integration
- Preliminary control variates to improve empirical regression methods
