MARCA: Markov chain analyzer, a software package for Markov modeling MARCA is a software package designed to facilitate the generation of large Markov chains and to compute transitent probability distributions of the chain at different times as well as its stationary probability vector. The software package MARCA is written in Fortran and has the following three segments: par 1. A Master Segment, which controls the operation of the package. par 2. The Second Segment deals with generation of the states of the system and the infinitesimal generation of matrix. par 3. The Third Segment derives and analyzes the stationary probability vector and the transient probability distributions.

References in zbMATH (referenced in 22 articles , 1 standard article )

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  1. Duff, Iain S.; Kaya, Kamer: Preconditioners based on strong subgraphs (2013)
  2. Pultarová, Ivana; Marek, Ivo: Convergence of multi-level iterative aggregation-disaggregation methods (2011)
  3. Kaynar, Bahar; Ridder, Ad: The cross-entropy method with patching for rare-event simulation of large Markov chains (2010)
  4. Migallón, Héctor; Migallón, Violeta; Penadés, Jose: Alternating two-stage methods for consistent linear systems with applications to the parallel solution of Markov chains (2010)
  5. Du, Xiuhong; Szyld, Daniel B.: Inexact GMRES for singular linear systems (2008)
  6. Borovac, Stefan: A graph based approach to the convergence of some iterative methods for singular M-matrices and Markov chains. (2006)
  7. Bru, Rafael; Pedroche, Francisco; Szyld, Daniel B.: Additive Schwarz iterations for Markov chains (2005)
  8. Pekergin, Nihal; Dayar, Tuğrul; Alparslan, Denizhan N.: Componentwise bounds for nearly completely decomposable Markov chains using stochastic comparison and reordering (2005)
  9. Buchholz, Peter; Dayar, Tuǧrul: Block SOR for Kronecker structured representations (2004)
  10. Fourneau, J.M.; Lecoz, M.; Quessette, F.: Algorithms for an irreducible and lumpable strong stochastic bound (2004)
  11. Kwiatkowska, Marta; Norman, Gethin; Parker, David: Probabilistic symbolic model checking with prism: a hybrid approach (2004) ioport
  12. Gusak, Oleg; Dayar, Tuğrul; Fourneau, Jean-Michel: Lumpable continuous-time stochastic automata networks. (2003)
  13. Marek, Ivo: Iterative aggregation/disaggregation methods for computing some characteristics of Markov chains. II: Fast convergence (2003)
  14. Marek, Ivo; Mayer, Petr: Convergence theory of some classes of iterative aggregation/disaggregation methods for computing stationary probability vectors of stochastic matrices (2003)
  15. Benzi, Michele; Tůma, Miroslav: A parallel solver for large-scale Markov chains (2002)
  16. Marek, Ivo; Mayer, Petr: Aggregation/disaggregation iterative methods applied to Leontev systems and Markov chains. (2002)
  17. Dayar, Tuugrul; Stewart, William J.: Comparison of partitioning techniques for two-level iterative solvers on large, sparse Markov chains (2000)
  18. Sidje, Roger B.; Stewart, William J.: A numerical study of large sparse matrix exponentials arising in Markov chains. (1999)
  19. Yamashita, Hideaki; Onvural, Raif O.: Allocation of buffer capacities in queueing networks with arbitrary topologies (1994)
  20. Haverkort, Boudewijn R.; Trivedi, Kishor S.: Specification techniques for Markov reward models (1993)

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