Large deviation asymptotics and control variates for simulating large functions
From MaRDI portal
Publication:2494582
DOI10.1214/105051605000000737zbMath1094.60017arXivmath/0603328OpenAlexW2122551798MaRDI QIDQ2494582
Publication date: 29 June 2006
Published in: The Annals of Applied Probability (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/math/0603328
Computational methods in Markov chains (60J22) Monte Carlo methods (65C05) Interacting random processes; statistical mechanics type models; percolation theory (60K35) Large deviations (60F10)
Related Items
Large deviations for the empirical mean of an M/M/\(1\) queue ⋮ Tail behaviour of the area under a random process, with applications to queueing systems, insurance and percolations ⋮ Large deviations for random dynamical systems and applications to hidden Markov models ⋮ The ODE method for stability of skip-free Markov chains with applications to MCMC ⋮ Linear variance bounds for particle approximations of time-homogeneous Feynman-Kac formulae ⋮ On the tail asymptotics of the area swept under the Brownian storage graph ⋮ Exponential transform of quadratic functional and multiplicative ergodicity of a Gauss-Markov process ⋮ Fundamental design principles for reinforcement learning algorithms
Cites Work
- Markov additive processes. I: Eigenvalue properties and limit theorems
- Markov additive processes. II: Large deviations
- Strong large deviation and local limit theorems
- Markov chains and stochastic stability
- Large deviation lower bounds for additive functionals of Markov processes
- Large deviations for empirical measures of Markov chains
- Large deviations and applications
- Large deviation lower bounds for arbitrary additive functionals of a Markov chain
- Some topics in regenerative steady-state simulation
- Computable bounds for geometric convergence rates of Markov chains
- Fluctuations of the entropy production in anharmonic chains
- In search of sensitivity in network optimization
- Essential spectral radius for Markov semigroups. I: Discrete time case
- Hoeffding's inequality for uniformly ergodic Markov chains
- Necessary conditions in limit theorems for cumulative processes.
- Large deviations asymptotics and the spectral theory of multiplicatively regular Markov proces\-ses
- On the central limit theorem for geometrically ergodic Markov chains
- Performance evaluation and policy selection in multiclass networks
- Spectral theory and limit theorems for geometrically ergodic Markov processes
- Multiplicative ergodicity and large deviations for an irreducible Markov chain.
- Worst-case large-deviation asymptotics with application to queueing and information theory
- A Liapounov bound for solutions of the Poisson equation
- On Deviations of the Sample Mean
- General Irreducible Markov Chains and Non-Negative Operators
- Control Variate Remedies
- A Fluid Heuristic for Minimizing Makespan in Job Shops
- Asymptotic evaluation of certain markov process expectations for large time. IV
- Inequalities in Theorems of Ergodicity and Stability for Markov Chains with Common Phase Space. I
- On ergodicity and recurrence properties of a Markov chain by an application to an open jackson network
- Asymptotic evaluation of certain markov process expectations for large time, II
- Asymptotic evaluation of certain Markov process expectations for large time—III
- On the Approximation of Complicated Dynamical Behavior
- Stability and convergence of moments for multiclass queueing networks via fluid limit models
- Duality and linear programs for stability and performance analysis of queuing networks and scheduling policies
- Workload models for stochastic networks: value functions and performance evaluation
- Approximating Martingales for Variance Reduction in Markov Process Simulation
- An introduction to the theory of large deviations
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
