Biips: Software for Bayesian Inference with Interacting Particle Systems. Biips is a software platform for automatic Bayesian inference with interacting particle systems. Biips allows users to define their statistical model in the probabilistic programming BUGS language, as well as to add custom functions or samplers within this language. Then it runs sequential Monte Carlo based algorithms (particle filters, particle independent Metropolis-Hastings, particle marginal Metropolis-Hastings) in a black-box manner so that to approximate the posterior distribution of interest as well as the marginal likelihood. The software is developed in C++ with interfaces with the softwares R, Matlab and Octave.
Keywords for this software
References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Johan Dahlin, Thomas B. Schön: Getting Started with Particle Metropolis-Hastings for Inference in Nonlinear Dynamical Models (2019) not zbMATH
- Nicholas Michaud, Perry de Valpine, Daniel Turek, Christopher J. Paciorek: Sequential Monte Carlo Methods in the nimble R Package (2017) arXiv
- Adrien Todeschini, Francois Caron, Marc Fuentes, Pierrick Legrand, Pierre Del Moral: Biips: Software for Bayesian Inference with Interacting Particle Systems (2014) arXiv
- Zhou Y: vSMC: Parallel Sequential Monte Carlo in C++ (2013) arXiv