Introduction | Methods | Package features | Examples with life course data | Conclusion | Notations

Introduction | Forward–Backward Algorithm | Viterbi Algorithm | Gradients

Introduction | Tools for visualizing multichannel sequence data | Tools for hidden Markov models | Helper tools

Introduction | Gaussian state space model | State space models for the exponential family | Residuals | Functionality of KFAS | Constructing common state space models with KFAS | Illustration | Other packages for non-Gaussian time series modelling | Discussion | Appendix: Filtering and smoothing recursions

Introduction | Illustration | Posterior predictive checks | Counterfactual predictions | Out-of-sample prediction | Extensions: Smoother effects and non-Gaussian models | Comparison with naive approach | Discussion | Acknowledgements | References

Introduction | $\psi$-APF | $\psi$-APF for non-linear Gaussian models | Illustrations | Non-linear transition equation | Non-linear observation equation | Discussion | References

Introduction | State space models with linear-Gaussian dynamics | Non-linear models | Time-discretised diffusion models | Markov chain Monte Carlo | Package functionality | Model building functions | Filtering and smoothing | Acknowledgements | References

Introduction | Example | Appendix

Introduction | Model in bssm | Markov chain Monte Carlo | Appendix

Introduction | Illustrations | Weighted quantiles | References

Model parameters | Tips for special cases | Restricted models | Tips for model estimation

Introduction | RAM algorithm | Illustration | Linking to other R packages | References