Geometric ergodicity in a weighted Sobolev space
DOI10.1214/19-AOP1364zbMath1456.60174arXiv1711.03652MaRDI QIDQ2184822
Adithya Devraj, Ioannis Kontoyiannis, Sean P. Meyn
Publication date: 29 May 2020
Published in: The Annals of Probability (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1711.03652
stochastic Lyapunov functionweighted Sobolev spaceMarkov chaindiscrete spectrumLyapunov exponentsensitivity process
Discrete-time Markov processes on general state spaces (60J05) Semigroups of nonlinear operators (47H20) Ergodic theory of linear operators (47A35) Ergodic theorems, spectral theory, Markov operators (37A30) Transition functions, generators and resolvents (60J35)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Hitting times, functional inequalities, Lyapunov conditions and uniform ergodicity
- On the Kantorovich-Rubinstein theorem
- Asymptotic coupling and a general form of Harris' theorem with applications to stochastic delay equations
- Lyapunov conditions for super Poincaré inequalities
- Lyapunov exponents and relative entropy for a stochastic flow of diffeomorphisms
- Exit probabilities and optimal stochastic control
- Uniformly integrable operators and large deviations for Markov processes
- Martingale problems for large deviations of Markov processes
- Large deviations asymptotics and the spectral theory of multiplicatively regular Markov proces\-ses
- On the Poisson equation and diffusion approximation. I
- Spectral theory and limit theorems for geometrically ergodic Markov processes
- Multiplicative ergodicity and large deviations for an irreducible Markov chain.
- Large and moderate deviations and exponential convergence for stochastic damping Hamiltonian systems.
- Transportation cost-information inequalities and applications to random dynamical systems and diffusions.
- Exponential and uniform ergodicity of Markov processes
- Geometric ergodicity and the spectral gap of non-reversible Markov chains
- Geometric convergence bounds for Markov chains in Wasserstein distance based on generalized drift and contraction conditions
- Approximating a diffusion by a finite-state hidden Markov model
- Nonasymptotic convergence analysis for the unadjusted Langevin algorithm
- Subgeometric rates of convergence of Markov processes in the Wasserstein metric
- Spectral gap of positive operators and applications
- Spectral gaps in Wasserstein distances and the 2D stochastic Navier-Stokes equations
- A Liapounov bound for solutions of the Poisson equation
- Stochastic simulation: Algorithms and analysis
- Central limit theorems for additive functionals of ergodic Markov diffusions processes
- Lyapunov Exponents for Finite State Nonlinear Filtering
- Markov Chains and Stochastic Stability
- Asymptotic evaluation of certain markov process expectations for large time. IV
- Asymptotic evaluation of certain markov process expectations for large time, II
- Asymptotic evaluation of certain Markov process expectations for large time—III
- Perturbation realization, potentials, and sensitivity analysis of Markov processes
- Quantitative Harris-type theorems for diffusions and McKean–Vlasov processes
- Differential Temporal Difference Learning
- Poisson's Equation in Nonlinear Filtering
- Control Techniques for Complex Networks
- Irreducible Markov Operators on C(S)
- Perturbation theory and finite Markov chains
- Bernstein Polynomials for Functions of Two Variables of Class C (k)
- On Two-Dimensional Bernstein Polynomials
This page was built for publication: Geometric ergodicity in a weighted Sobolev space
