• PRISM

  • Referenced in 416 articles [sw01186]
  • PRISM supports three probabilistic models: discrete-time Markov chains, Markov decision processes and continuous-time ... Markov chains. Analysis is performed through model checking such systems against specifications written...
  • GMRFLib

  • Referenced in 286 articles [sw06641]
  • Gaussian Markov random fields. Theory and applications. Researchers in spatial statistics and image analysis ... familiar with Gaussian Markov Random Fields (GMRFs), and they are traditionally among ... comprehensive reference on the subject.par Gaussian Markov Random Fields: Theory and Applications provides such ... which statistical inference is only possible using Markov Chain Monte Carlo (MCMC) techniques. The preeminent...
  • CODA

  • Referenced in 294 articles [sw04290]
  • MCMC , Output analysis and diagnostics for Markov Chain Monte Carlo simulations. Provides functions for summarizing ... plotting the output from Markov Chain Monte Carlo (MCMC) simulations, as well as diagnostic tests ... convergence to the equilibrium distribution of the Markov chain...
  • BUGS

  • Referenced in 364 articles [sw07885]
  • Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. The project...
  • spBayes

  • Referenced in 330 articles [sw10160]
  • Unfortunately, fitting such models involves computationally intensive Markov chain Monte Carlo (MCMC) methods whose efficiency...
  • Expokit

  • Referenced in 179 articles [sw00258]
  • critical importance in the area of Markov chains and furthermore, the computed solution is subject ... computation of transient states of Markov chains...
  • JAGS

  • Referenced in 209 articles [sw08040]
  • analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike...
  • MCQueue

  • Referenced in 139 articles [sw05198]
  • MCQueue: educational software for Markov Chains and Queues (non-commercial use) This software package contains ... analysis of discrete-time and continuous-time Markov chains up to 100 states. The other...
  • PEPA

  • Referenced in 116 articles [sw10692]
  • PEPA editor and performance analysers which use Markov chain or ODE methods or simulation. Performance...
  • MLwiN

  • Referenced in 104 articles [sw04837]
  • uses both maximum likelihood estimation and Markov Chain Monte Carlo (MCMC) methods. MLwiN is based...
  • SHOGUN

  • Referenced in 101 articles [sw03517]
  • models such as support vector machines, hidden Markov models, multiple kernel learning, linear discriminant analysis...
  • MRMC

  • Referenced in 70 articles [sw04129]
  • probabilistic model checker MRMC. The Markov Reward Model Checker (MRMC) is a software tool ... time-bounded reachability analysis for continuous-time Markov decision processes (CTMDPs) and CSL model checking...
  • boa

  • Referenced in 91 articles [sw04493]
  • diagnostics and statistical and graphical analysis of Markov chain Monte Carlo sampling output...
  • msm

  • Referenced in 48 articles [sw08096]
  • package msm: Multi-state Markov and hidden Markov models in continuous time. Functions for fitting ... general continuous-time Markov and hidden Markov multi-state models to longitudinal data. A variety ... continuously-observed processes, and censored states. Both Markov transition rates and the hidden Markov output...
  • Gibbsit

  • Referenced in 80 articles [sw25318]
  • achieve a specified accuracy level in Markov chain Monte Carlo. An S translation...
  • OpenBUGS

  • Referenced in 74 articles [sw08316]
  • expert system’, which determines an appropriate MCMC (Markov chain Monte Carlo) scheme (based...
  • R-INLA

  • Referenced in 63 articles [sw08014]
  • results are compared with that obtained by Markov chain Monte Carlo, showing similar accuracy with...
  • SHARPE

  • Referenced in 42 articles [sw03100]
  • networks and state-space ones such as Markov and semi-Markov reward models as well...
  • pomp

  • Referenced in 41 articles [sw10664]
  • package pomp: Statistical Inference for Partially Observed Markov Processes. Tools for working with partially observed ... Markov processes (POMPs, AKA stochastic dynamical systems, state-space models). ’pomp’ provides facilities for implementing...
  • RStan

  • Referenced in 57 articles [sw13990]
  • that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference...