The conjugate gradient method for computing all the extremal stationary probability vectors of a stochastic matrix

DOI10.1007/BF02481090zbMath0569.60069OpenAlexW2038257553MaRDI QIDQ1060776

Kunio Tanabe

Publication date: 1985

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02481090

zbMATH Keywords

Moore- Penrose inversestationary probability vectorsThe conjugate gradient method

Mathematics Subject Classification ID

Stationary stochastic processes (60G10) Queueing theory (aspects of probability theory) (60K25) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Transition functions, generators and resolvents (60J35) Stochastic matrices (15B51)

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Cites Work

• The conjugate gradient method for computing all the extremal stationary probability vectors of a stochastic matrix
• On the Fixed Point Probability Vector of Regular or Ergodic Transition Matrices
• On the Convergence of the Conjugate Gradient Method for Singular Linear Operator Equations
• Methods of conjugate gradients for solving linear systems
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