Exponential convergence rates for stochastically ordered Markov processes under perturbation
From MaRDI portal
Publication:2338184
DOI10.1016/j.sysconle.2019.104515zbMath1427.93223arXiv1810.07732OpenAlexW2971745727WikidataQ115566765 ScholiaQ115566765MaRDI QIDQ2338184
Saurabh Amin, Julia Gaudio, Patrick Jaillet
Publication date: 21 November 2019
Published in: Systems \& Control Letters (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1810.07732
Queues and service in operations research (90B22) Stochastic systems in control theory (general) (93E03)
Related Items (1)
Cites Work
- Subgeometric ergodicity for continuous-time Markov chains
- Determining an adequate probe separation for estimating the arrival rate in an \(M/D/1\) queue using single-packet probing
- Stochastic inequalities on partially ordered spaces
- Quantitative bounds on convergence of time-inhomogeneous Markov chains
- 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
- Explicit Rates of Exponential Convergence for Reflected Jump-Diffusions on the Half-Line
- Subgeometric rates of convergence for a class of continuous-time Markov process
- COMPUTABLE STRONGLY ERGODIC RATES OF CONVERGENCE FOR CONTINUOUS-TIME MARKOV CHAINS
- Technical note: Traffic intensity estimation
- Conditions for exponential ergodicity and bounds for the decay parameter of a birth-death process
- Rates of convergence of stochastically monotone and continuous time Markov models
This page was built for publication: Exponential convergence rates for stochastically ordered Markov processes under perturbation