A weak perturbation theory for approximations of invariant measures in M/G/1 model
From MaRDI portal
Publication:4634334
DOI10.1051/ro/2018027zbMath1430.60075OpenAlexW2802655275WikidataQ129898872 ScholiaQ129898872MaRDI QIDQ4634334
Badredine Isaadi, Karim Abbas, Djamil Aissani
Publication date: 7 May 2019
Published in: RAIRO - Operations Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1051/ro/2018027
Queueing theory (aspects of probability theory) (60K25) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Augmented truncation approximations of discrete-time Markov chains
- Monotone infinite stochastic matrices and their augmented truncations
- Computing the stationary distribution for infinite Markov chains
- Perturbation analysis of the \(\mathrm{GI}/\mathrm{M}/s\) queue
- On the approximation of the stationary distribution of a monotone stochastic Markov chain
- Approximating Markov chains and \(V\)-geometric ergodicity via weak perturbation theory
- Non-negative matrices and Markov chains.
- Rigorous numerical investigation of the statistical properties of piecewise expanding maps. A feasibility study
- Markov Chains and Stochastic Stability
- Approximation of the invariant probability measure of an infinite stochastic matrix
- Truncation approximations of invariant measures for Markov chains
- A Perturbation Theory for Ergodic Markov Chains and Application to Numerical Approximations
- Regular Perturbation of V-Geometrically Ergodic Markov Chains
- The Matrix Eigenvalue Problem
- Approximating the stationary distribution of an infinite stochastic matrix
This page was built for publication: A weak perturbation theory for approximations of invariant measures in M/G/1 model