Man pages for bssm
Bayesian Inference of Non-Linear and Non-Gaussian State Space Models
| ar1_lg | Univariate Gaussian model with AR(1) latent process |
| ar1_ng | Non-Gaussian model with AR(1) latent process |
| as_bssm | Convert KFAS Model to bssm Model |
| as.data.frame.mcmc_output | Convert MCMC Output to data.frame |
| as_draws-mcmc_output | Convert 'run_mcmc' Output to 'draws_df' Format |
| asymptotic_var | Asymptotic Variance of IS-type Estimators |
| bootstrap_filter | Bootstrap Filtering |
| bsm_lg | Basic Structural (Time Series) Model |
| bsm_ng | Non-Gaussian Basic Structural (Time Series) Model |
| bssm | Bayesian Inference of State Space Models |
| bssm_prior | Prior objects for bssm models |
| check_diagnostics | Quick Diagnostics Checks for 'run_mcmc' Output |
| cpp_example_model | Example C++ Codes for Non-Linear and SDE Models |
| drownings | Deaths by drowning in Finland in 1969-2019 |
| ekf | (Iterated) Extended Kalman Filtering |
| ekf_smoother | Extended Kalman Smoothing |
| ekpf_filter | Extended Kalman Particle Filtering |
| estimate_ess | Effective Sample Size for IS-type Estimators |
| exchange | Pound/Dollar daily exchange rates |
| expand_sample | Expand the Jump Chain representation |
| fitted.mcmc_output | Fitted for State Space Model |
| gaussian_approx | Gaussian Approximation of Non-Gaussian/Non-linear State Space... |
| iact | Integrated Autocorrelation Time |
| importance_sample | Importance Sampling from non-Gaussian State Space Model |
| kfilter | Kalman Filtering |
| logLik_bssm | Extract Log-likelihood of a State Space Model of class... |
| negbin_model | Estimated Negative Binomial Model of Helske and Vihola (2021) |
| negbin_series | Simulated Negative Binomial Time Series Data |
| particle_smoother | Particle Smoothing |
| plot.mcmc_output | Trace and Density Plots for 'mcmc_output' |
| poisson_series | Simulated Poisson Time Series Data |
| post_correct | Run Post-correction for Approximate MCMC using psi-APF |
| predict.mcmc_output | Predictions for State Space Models |
| print.mcmc_output | Print Results from MCMC Run |
| run_mcmc | Bayesian Inference of State Space Models |
| sim_smoother | Simulation Smoothing |
| smoother | Kalman Smoothing |
| ssm_mlg | General multivariate linear Gaussian state space models |
| ssm_mng | General Non-Gaussian State Space Model |
| ssm_nlg | General multivariate nonlinear Gaussian state space models |
| ssm_sde | Univariate state space model with continuous SDE dynamics |
| ssm_ulg | General univariate linear-Gaussian state space models |
| ssm_ung | General univariate non-Gaussian state space model |
| suggest_N | Suggest Number of Particles for psi-APF Post-correction |
| summary.mcmc_output | Summary Statistics of Posterior Samples |
| svm | Stochastic Volatility Model |
| ukf | Unscented Kalman Filtering |
