Iterative aggregation/disaggregation method for computing stationary probability vectors of Markov type operators

DOI10.1016/0898-1221(95)00213-8zbMath0874.65108OpenAlexW2079267753MaRDI QIDQ1361268

Ivo Marek, Petr Mayer

Publication date: 10 November 1997

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0898-1221(95)00213-8

zbMATH Keywords

global convergencenumerical experimentsstochastic matrixMarkov type operatorstationary probability vectorsiterative aggregation/disaggregation methodsLeontieff type models

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Diffusion processes (60J60) Numerical solutions to equations with linear operators (65J10) Equations and inequalities involving linear operators, with vector unknowns (47A50) Probabilistic methods, stochastic differential equations (65C99)

Related Items (3)

Quasi-birth-and-death processes, level-geometric distributions. An aggregation/disaggregation approach ⋮ A multi-cluster time aggregation approach for Markov chains ⋮ A visibility graph averaging aggregation operator

Cites Work

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• A local convergence proof for the iterative aggregation method
• Perturbation of spectral inverses applied to a boundary layer phenomenon arising in chemical networks
• Local convergence of the (exact and inexact) iterative aggregation method for linear systems and Markov operators
• A nonlinear model involving \(M\)-operators. An amplification effect measured in the cascade of vision
• Iterative aggregation/disaggregation techniques for nearly uncoupled markov chains
• Semi-Iterative and Iterative Methods for Singular M-Matrices
• Aggregation in Leontief Matrices and the Labour Theory of Value
• An Implementation of Tarjan's Algorithm for the Block Triangularization of a Matrix
• Iterative and Semi-Iterative Methods for Computing Stationary Probability Vectors of Markov Operators
• A Boundary Layer Phenomenon for Linear Systems with a Rank Deficient Matrix

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