Bayesian Inference of State Space Models

Efficient methods for Bayesian inference of state space models via particle Markov chain Monte Carlo and importance sampling type corrected Markov chain Monte Carlo. Gaussian, Poisson, binomial, or negative binomial observation densities and Gaussian state dynamics, as well as general non-linear Gaussian models are supported.


Reference manual

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0.1.1-1 by Jouni Helske, 2 months ago

Browse source code at

Authors: Jouni Helske, Matti Vihola

Documentation:   PDF Manual  

GPL (>= 2) license

Imports coda, diagis, ggplot2, Rcpp

Suggests KFAS, knitr, rmarkdown, testthat, bayesplot

Linking to BH, Rcpp, RcppArmadillo, ramcmc, sitmo

System requirements: C++11

See at CRAN