bssm: run_mcmc – R documentation

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run_mcmc

Bayesian Inference of State Space Models

Description

Adaptive Markov chain Monte Carlo simulation of state space models using Robust Adaptive Metropolis algorithm by Vihola (2012). See specific methods for various model types for details.

Usage

run_mcmc(model, iter, ...)

Arguments

`model`	State space model model of `bssm` package.
`iter`	Number of MCMC iterations.
`...`	Parameters to specific methods. See `run_mcmc.gaussian`, `run_mcmc.nongaussian`, `run_mcmc.ssm_nlg`, and `run_mcmc.ssm_sde` for details.

References

Matti Vihola (2012). "Robust adaptive Metropolis algorithm with coerced acceptance rate". Statistics and Computing, Volume 22, Issue 5, pages 997–1008.

bssm

Bayesian Inference of Non-Linear and Non-Gaussian State Space Models

v1.1.4

GPL (>= 2)

Authors

Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>), Matti Vihola [aut] (<https://orcid.org/0000-0002-8041-7222>)

Initial release

2021-04-13