Variational principles for asymptotic variance of general Markov processes
From MaRDI portal
Publication:2690111
DOI10.1007/s10114-022-1226-zOpenAlexW3169035902WikidataQ114228355 ScholiaQ114228355MaRDI QIDQ2690111
Tao Wang, Lu-Jing Huang, Yong Hua Mao
Publication date: 15 March 2023
Published in: Acta Mathematica Sinica. English Series (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2106.00324
comparison theoremMarkov processasymptotic variancesemi-Dirichlet formvariational formulamean exit time
Continuous-time Markov processes on general state spaces (60J25) Diffusion processes (60J60) Dirichlet form methods in Markov processes (60J46)
Cites Work
- Unnamed Item
- Variance reduction using nonreversible Langevin samplers
- Non-reversible Metropolis-Hastings
- Comparison of asymptotic variances of inhomogeneous Markov chains with application to Markov chain Monte Carlo methods
- Variance reduction for diffusions
- Variance bounding Markov chains
- Central limit theorem for additive functionals of reversible Markov processes and applications to simple exclusions
- Introduction to the theory of (non-symmetric) Dirichlet forms
- A note on Metropolis-Hastings kernels for general state spaces
- Geometric ergodicity and hybrid Markov chains
- On the central limit theorem for geometrically ergodic Markov chains
- Exponential convergence of Markovian semigroups and their spectra on \(L^p\)-spaces
- Variational formulas for the exit time of hunt processes generated by semi-Dirichlet forms
- Minimising MCMC variance via diffusion limits, with an application to simulated tempering
- Accelerating reversible Markov chains
- Irreversible Langevin samplers and variance reduction: a large deviations approach
- Optimum Monte-Carlo sampling using Markov chains
- Ergodicity for Infinite Dimensional Systems
- On the Optimal Transition Matrix for Markov Chain Monte Carlo Sampling
- Fluctuations in Markov Processes
- Elliptic equations for invariant measures on finite and infinite dimensional manifolds
- The central limit theorem for Markov chains with normal transition operators, started at a point
This page was built for publication: Variational principles for asymptotic variance of general Markov processes