Explicit convergence rates for the \(M/G/1\) queue under perturbation
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Publication:6096341
DOI10.1016/j.amc.2023.128203MaRDI QIDQ6096341
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Publication date: 12 September 2023
Published in: Applied Mathematics and Computation (Search for Journal in Brave)
Markov processes (60Jxx) Probability theory and stochastic processes (60-XX) Special processes (60Kxx)
Cites Work
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- Markov chains and stochastic stability
- Convergence rates in strong ergodicity for Markov processes
- Continuous-time Markov chains. An applications-oriented approach
- Renewal theory and computable convergence rates for geometrically erdgodic Markov chains
- Quantitative convergence rates of Markov chains: A simple account
- Computable exponential convergence rates for stochastically ordered Markov processes
- Exponential convergence rates for stochastically ordered Markov processes under perturbation
- Explicit convergence rates of the embedded \(\mathrm{M}/\mathrm{G}/1\) queue
- Error Bounds for Augmented Truncations of Discrete-Time Block-Monotone Markov Chains under Subgeometric Drift Conditions
- Perturbation of the stationary distribution measured by ergodicity coefficients
- Subgeometric Rates of Convergence of f-Ergodic Markov Chains
- Eigenvalues, Inequalities, and Ergodic Theory
- Explicit criteria for several types of ergodicity of the embedded M/G/1 and GI/M/n queues
- Strong ergodicity for Markov processes by coupling methods
- Minorization Conditions and Convergence Rates for Markov Chain Monte Carlo
- Error Bounds for Augmented Truncations of Discrete-Time Block-Monotone Markov Chains under Geometric Drift Conditions
- Several Types of Ergodicity for M/G/1-Type Markov Chains and Markov Processes
- Stochastic Processes Occurring in the Theory of Queues and their Analysis by the Method of the Imbedded Markov Chain
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