bssm-package |
Bayesian Inference of State Space Models |
ar1_lg |
Univariate Gaussian model with AR(1) latent process |
ar1_ng |
Non-Gaussian model with AR(1) latent process |
as.data.frame.mcmc_output |
Convert MCMC Output to data.frame |
asymptotic_var |
Asymptotic Variance of IS-type Estimators |
as_bssm |
Convert KFAS Model to bssm Model |
as_draws |
Convert 'run_mcmc' Output to 'draws_df' Format |
as_draws.mcmc_output |
Convert 'run_mcmc' Output to 'draws_df' Format |
as_draws_df |
Convert 'run_mcmc' Output to 'draws_df' Format |
as_draws_df.mcmc_output |
Convert 'run_mcmc' Output to 'draws_df' Format |
bootstrap_filter |
Bootstrap Filtering |
bootstrap_filter.lineargaussian |
Bootstrap Filtering |
bootstrap_filter.nongaussian |
Bootstrap Filtering |
bootstrap_filter.ssm_nlg |
Bootstrap Filtering |
bootstrap_filter.ssm_sde |
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 |
bssm_prior_list |
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_fast_smoother |
Extended Kalman Smoothing |
ekf_smoother |
Extended Kalman Smoothing |
ekpf_filter |
Extended Kalman Particle Filtering |
ekpf_filter.ssm_nlg |
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 |
fast_smoother |
Kalman Smoothing |
fast_smoother.lineargaussian |
Kalman Smoothing |
fitted.mcmc_output |
Fitted for State Space Model |
gamma |
Prior objects for bssm models |
gamma_prior |
Prior objects for bssm models |
gaussian_approx |
Gaussian Approximation of Non-Gaussian/Non-linear State Space Model |
gaussian_approx.nongaussian |
Gaussian Approximation of Non-Gaussian/Non-linear State Space Model |
gaussian_approx.ssm_nlg |
Gaussian Approximation of Non-Gaussian/Non-linear State Space Model |
halfnormal |
Prior objects for bssm models |
halfnormal_prior |
Prior objects for bssm models |
iact |
Integrated Autocorrelation Time |
importance_sample |
Importance Sampling from non-Gaussian State Space Model |
importance_sample.nongaussian |
Importance Sampling from non-Gaussian State Space Model |
kfilter |
Kalman Filtering |
kfilter.lineargaussian |
Kalman Filtering |
kfilter.nongaussian |
Kalman Filtering |
logLik.lineargaussian |
Extract Log-likelihood of a State Space Model of class 'bssm_model' |
logLik.nongaussian |
Extract Log-likelihood of a State Space Model of class 'bssm_model' |
logLik.ssm_nlg |
Extract Log-likelihood of a State Space Model of class 'bssm_model' |
logLik.ssm_sde |
Extract Log-likelihood of a State Space Model of class 'bssm_model' |
negbin_model |
Estimated Negative Binomial Model of Helske and Vihola (2021) |
negbin_series |
Simulated Negative Binomial Time Series Data |
normal |
Prior objects for bssm models |
normal_prior |
Prior objects for bssm models |
particle_smoother |
Particle Smoothing |
particle_smoother.lineargaussian |
Particle Smoothing |
particle_smoother.nongaussian |
Particle Smoothing |
particle_smoother.ssm_nlg |
Particle Smoothing |
particle_smoother.ssm_sde |
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 |
Predictions for State Space Models |
predict.mcmc_output |
Predictions for State Space Models |
print.mcmc_output |
Print Results from MCMC Run |
run_mcmc |
Bayesian Inference of State Space Models |
run_mcmc.lineargaussian |
Bayesian Inference of State Space Models |
run_mcmc.nongaussian |
Bayesian Inference of State Space Models |
run_mcmc.ssm_nlg |
Bayesian Inference of State Space Models |
run_mcmc.ssm_sde |
Bayesian Inference of State Space Models |
sim_smoother |
Simulation Smoothing |
sim_smoother.lineargaussian |
Simulation Smoothing |
sim_smoother.nongaussian |
Simulation Smoothing |
smoother |
Kalman Smoothing |
smoother.lineargaussian |
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 |
tnormal |
Prior objects for bssm models |
tnormal_prior |
Prior objects for bssm models |
ukf |
Unscented Kalman Filtering |
uniform |
Prior objects for bssm models |
uniform_prior |
Prior objects for bssm models |