JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: (1) To have a cross-platform engine for the BUGS language. (2) To be extensible, allowing users to write their own functions, distributions and samplers. (3) To be a plaftorm for experimentation with ideas in Bayesian modelling. JAGS is licensed under the GNU General Public License. You may freely modify and redistribute it under certain conditions (see the file COPYING for details).

References in zbMATH (referenced in 190 articles )

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  6. Miller, David L.; Glennie, Richard; Seaton, Andrew E.: Understanding the stochastic partial differential equation approach to smoothing (2020)
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  9. Robert J. B. Goudie, Rebecca M. Turner, Daniela De Angelis, Andrew Thomas: MultiBUGS: A Parallel Implementation of the BUGS Modeling Framework for Faster Bayesian Inference (2020) not zbMATH
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  16. Arellano-Valle, Reinaldo B.; Contreras-Reyes, Javier E.; Quintero, Freddy O. López; Valdebenito, Abel: A skew-normal dynamic linear model and Bayesian forecasting (2019)
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  19. Finke, Axel; King, Ruth; Beskos, Alexandros; Dellaportas, Petros: Efficient sequential Monte Carlo algorithms for integrated population models (2019)
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