Wen, Chun; Huang, Ting-Zhu; Wu, De-An; Li, Liang The finest level acceleration of multilevel aggregation for Markov chains. (English) Zbl 1248.65015 Int. J. Numer. Anal. Model., Ser. B 2, No. 1, 27-41 (2011). Summary: We consider a class of new accelerated multilevel aggregation methods using two polynomial-type vector extrapolation methods, namely the reduced rank extrapolation (RRE) and the generalization of quadratic extrapolation (GQE) methods. We show how to combine the multilevel aggregation methods with the RRE and GQE algorithms on the finest level in order to speed up the numerical computation of the stationary probability vector for an irreducible Markov chain. Numerical experiments on typical Markov chain problems are reported to illustrate the efficiency of the accelerated multilevel aggregation methods. Cited in 3 Documents MSC: 65C40 Numerical analysis or methods applied to Markov chains 60J22 Computational methods in Markov chains Keywords:Markov chains; multilevel aggregation; acceleration; vector extrapolation methods; algorithm; numerical examples PDFBibTeX XMLCite \textit{C. Wen} et al., Int. J. Numer. Anal. Model., Ser. B 2, No. 1, 27--41 (2011; Zbl 1248.65015)