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  2. Stan (software) - Wikipedia

    en.wikipedia.org/wiki/Stan_(software)

    Stan: A probabilistic programming language for Bayesian inference and optimization, Journal of Educational and Behavioral Statistics. Hoffman, Matthew D., Bob Carpenter, and Andrew Gelman (2012). Stan, scalable software for Bayesian modeling Archived 2015-01-21 at the Wayback Machine, Proceedings of the NIPS Workshop on Probabilistic Programming.

  3. Bayesian inference using Gibbs sampling - Wikipedia

    en.wikipedia.org/wiki/Bayesian_inference_using...

    Bayesian inference using Gibbs sampling (BUGS) is a statistical software for performing Bayesian inference using Markov chain Monte Carlo (MCMC) methods. It was developed by David Spiegelhalter at the Medical Research Council Biostatistics Unit in Cambridge in 1989 and released as free software in 1991.

  4. Category:Free Bayesian statistics software - Wikipedia

    en.wikipedia.org/wiki/Category:Free_Bayesian...

    Download as PDF; Printable version; ... Free and open-source software portal; Pages in category "Free Bayesian statistics software" The following 9 pages are in this ...

  5. OpenBUGS - Wikipedia

    en.wikipedia.org/wiki/OpenBUGS

    OpenBUGS is a software application for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. OpenBUGS is the open source variant of WinBUGS (Bayesian inference Using Gibbs Sampling). It runs under Microsoft Windows and Linux, as well as from inside the R statistical package.

  6. Bayesian statistics - Wikipedia

    en.wikipedia.org/wiki/Bayesian_statistics

    Bayesian statistics (/ ˈ b eɪ z i ə n / BAY-zee-ən or / ˈ b eɪ ʒ ən / BAY-zhən) [1] is a theory in the field of statistics based on the Bayesian interpretation of probability, where probability expresses a degree of belief in an event. The degree of belief may be based on prior knowledge about the event, such as the results of previous ...

  7. Bayesian programming - Wikipedia

    en.wikipedia.org/wiki/Bayesian_programming

    Bayesian programming [2] is a formal and concrete implementation of this "robot". Bayesian programming may also be seen as an algebraic formalism to specify graphical models such as, for instance, Bayesian networks, dynamic Bayesian networks, Kalman filters or hidden Markov models.

  8. Bayes error rate - Wikipedia

    en.wikipedia.org/wiki/Bayes_error_rate

    This statistics -related article is a stub. You can help Wikipedia by expanding it.

  9. Test functions for optimization - Wikipedia

    en.wikipedia.org/wiki/Test_functions_for...

    The test functions used to evaluate the algorithms for MOP were taken from Deb, [4] Binh et al. [5] and Binh. [6] The software developed by Deb can be downloaded, [ 7 ] which implements the NSGA-II procedure with GAs, or the program posted on Internet, [ 8 ] which implements the NSGA-II procedure with ES.