bssm: Bayesian Inference of Non-linear and Non-Gaussian State Space Models in R

@article{Helske2021bssmBI,
  title={bssm: Bayesian Inference of Non-linear and Non-Gaussian State Space Models in R},
  author={Jouni Helske and Matti Vihola},
  journal={R J.},
  year={2021},
  volume={13},
  pages={471}
}
We present an R package bssm for Bayesian non-linear/non-Gaussian state space modelling. Unlike the existing packages, bssm allows for easy-to-use approximate inference based on Gaussian approximations such as the Laplace approximation and the extended Kalman filter. The package accommodates also discretely observed latent diffusion processes. The inference is based on fully automatic, adaptive Markov chain Monte Carlo (MCMC) on the hyperparameters, with optional importance sampling post… 

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