We consider iterative methods for t;le minimal nonnegativc :~oiu)i()n of the matrix equation G = ~, (), ,G', where the matrices ,4, are nonnegative and \'~ ,)..I, is stocha:4ic. Convergence theory lbr an 'inversion frec algorithm is established. The convergence rale of this algorithm is sho,s'.i ~o
Algebraic Schwarz methods for the numerical solution of Markov chains
β Scribed by Ivo Marek; Daniel B. Szyld
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 222 KB
- Volume
- 386
- Category
- Article
- ISSN
- 0024-3795
No coin nor oath required. For personal study only.
β¦ Synopsis
The convergence of additive and multiplicative Schwarz methods for computing certain characteristics of Markov chains such as stationary probability vectors and mean first passage matrices is studied. The main result is a convergence theorem for multiplicative Schwarz iterations when applied to singular systems. As a byproduct, a convergence result for alternating iterations is also obtained. It is also shown that, when the Markov chain is ergodic, additive and multiplicative Schwarz methods can be applied to the nonsingular systems that result from reducing the equations. The so-called coarse grid corrections are also studied.
π SIMILAR VOLUMES
We discuss the asymptotic validity of confidence intervals for quantiles of performance variables when simulating a Markov chain. We show that a batch quantile methodology (similar to the batch means method) can be applied to obtain confidence intervals that are asymptotically valid under mild assum