Preconditioned Krylov Subspace Methods for the Numerical Solution of Markov Chains

Yousef Saad
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Yousef Saad: University of Minnesota, Department of Computer Science

Chapter 4 in Computations with Markov Chains, 1995, pp 49-64 from Springer

Abstract: Abstract In a general projection technique the original matrix problem of size N is approximated by one of dimension m, typically much smaller than N. A particularly successful class of techniques based on this principle is that of Krylov subspace methods which utilise subspaces of the form span{v, Av,…., Am-1 v}. This general principle can be used to solve linear systems and eigenvalue problems which arise when computing stationary probability distributions of Markov chains. It can also be used to approximate the product of the exponential of a matrix by a vector as occurs when following the solutions of transient models. In this paper we give an overview of these ideas and discuss preconditioning techniques which constitute an essential ingredient in the success of Krylov subspace methods.

Keywords: Conjugate Gradient Method; Krylov Subspace; Krylov Subspace Method; Nonsymmetric Linear System; Minimum Residual Method (search for similar items in EconPapers)
Date: 1995
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4615-2241-6_4

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DOI: 10.1007/978-1-4615-2241-6_4

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