Modeling and analysis of communication systems based on computational methods for Markov chains
IEEE Journal on Selected Areas in Communications, 1990 The authors describe a computational approach for modeling and analyzing modern communication systems based on numerical methods for Markov chains. Advanced direct and iterative procedures for the calculation of the stationary distribution of a homogeneous discrete- or continuous-time Markov chain with finite state space are presented.
Udo R. Krieger +2 more
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Computation of Expectations by Markov Chain Monte Carlo Methods [PDF]
, 2014 Markov chain Monte Carlo (MCMC) methods are a very versatile and widely used tool to compute integrals and expectations. In this short survey we focus on error bounds, rules for choosing the burn in, high dimensional problems and tractability versus curse of dimension.
Erich Novak, Daniel Rudolf
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Imprecise Continuous-Time Markov Chains: Efficient Computational Methods with Guaranteed Error Bounds [PDF]
, 2017 45 pages, 12 of which constitute the main text, and 32 of which constitute an appendix with proofs and additional material. 1 table. Conference paper (ISIPTA'17). Proposition 11 turned out to be incorrect; we have added a counterexample that demonstrates this in the latest ...
Alexander Erreygers, Jasper De Bock
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Computation of identity by descent probabilities conditional on DNA markers via a Monte Carlo Markov Chain method [PDF]
Genetics Selection Evolution, 2000 The accurate estimation of the probability of identity by descent (IBD) at loci or genome positions of interest is paramount to the genetic study of quantitative and disease resistance traits. We present a Monte Carlo Markov Chain method to compute IBD probabilities between individuals conditional on DNA markers and on pedigree information.
Miguel Pérez‐Enciso +2 more
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An introduction to computational complexity in Markov Chain Monte Carlo methods [PDF]
, 2020 The aim of this work, is to give an introduction to the theoretical background and computational complexity of Markov chain Monte Carlo methods. Most of the mathematical results related to the convergence are not found in most of the statistical references, and computational complexity is still open question for most of the MCMC methods.
Izhar Asael Alonzo Matamoros
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Linear least square method for the computation of the mean first passage times of ergodic markov chains [PDF]
Journal of Advances in Mathematics and Computer Science, 2018 An efficient and accurate iterative scheme for the computation of the mean first passage times (MFPTs) of ergodic Markov chains has been presented. Firstly, the computation problem of MFPTs is transformed into a set of linear equations. It has been proven that each of these equations is compatible and their minimal norm solutions constitute MFPTs.
Yaming Chen
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On Stochastic Error and Computational Efficiency of the Markov Chain Monte Carlo Method [PDF]
Communications in Computational Physics, 2014 In Markov Chain Monte Carlo (MCMC) simulations, the thermal equilibria quantities are estimated by ensemble average over a sample set containing a large number of correlated samples. These samples are selected in accordance with the probability distribution function, known from the partition function of equilibrium state. As the stochastic error of the
Jun Li +3 more
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Bayesian Computation Via the Gibbs Sampler and Related Markov Chain Monte Carlo Methods
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1993 SUMMARY The use of the Gibbs sampler for Bayesian computation is reviewed and illustrated in the context of some canonical examples. Other Markov chain Monte Carlo simulation methods are also briefly described, and comments are made on the advantages of sample-based approaches for Bayesian inference summaries.
A. F. M. Smith, Gareth O. Roberts
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Computational methods for a copula-based Markov chain model with a binomial time series
Communications in Statistics - Simulation and Computation, 2022 Xin-Wei Huang, Takeshi Emura
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About Some Iterative Synchronous and Asynchronous Methods for Markov Chain Distribution Computation
IFAC Proceedings Volumes, 1987 Abstract This paper reports on some experiments of parallel processing on a multiprocessor for the numerical computation of the stationary probabilities distribution of the finite state discrete Markov Chain associated to a circuit switched telecommunication network.
J. Bernussou, F. Le Gall, G. Authié
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