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bssm (version 1.0.0)

Bayesian Inference of Non-Gaussian State Space Models

Description

Efficient methods for Bayesian inference of state space models via particle Markov chain Monte Carlo (MCMC) and MCMC based on parallel importance sampling type weighted estimators (Vihola, Helske, and Franks, 2020, ). Gaussian, Poisson, binomial, negative binomial, and Gamma observation densities and basic stochastic volatility models with Gaussian state dynamics, as well as general non-linear Gaussian models and discretised diffusion models are supported.

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Version

Install

install.packages('bssm')

Monthly Downloads

1,123

Version

1.0.0

License

GPL (>= 2)

Maintainer

Jouni Helske

Last Published

June 9th, 2020

Functions in bssm (1.0.0)

drownings

Deaths by drowning in Finland in 1969-2014
ekpf_filter

Extended Kalman Particle Filtering
bsm_ng

Non-Gaussian Basic Structural (Time Series) Model
uniform

Prior objects for bssm models
logLik.ssm_nlg

Log-likelihood of a Non-linear State Space Model
logLik.ssm_sde

Log-likelihood of a State Space Model with SDE dynamics
logLik.gaussian

Log-likelihood of a Gaussian State Space Model
kfilter

Kalman Filtering
ar1_ng

Non-Gaussian model with AR(1) latent process
ar1_lg

Univariate Gaussian model with AR(1) latent process
predict.mcmc_output

Predictions for State Space Models
print.mcmc_output

Print Results from MCMC Run
particle_smoother

Particle Smoothing
bsm_lg

Basic Structural (Time Series) Model
bootstrap_filter

Bootstrap Filtering
ssm_mlg

General multivariate linear Gaussian state space models
run_mcmc

Bayesian Inference of State Space Models
ssm_mng

General Non-Gaussian State Space Model
sim_smoother

Simulation Smoothing
bssm

Bayesian Inference of State Space Models
poisson_series

Simulated Poisson time series data
exchange

Pound/Dollar daily exchange rates
fast_smoother

Kalman Smoothing
ssm_ulg

General univariate linear-Gaussian state space models
ssm_ung

General univariate non-Gaussian state space model
ukf

Unscented Kalman Filtering
importance_sample

Importance Sampling from non-Gaussian State Space Model
ssm_nlg

General multivariate nonlinear Gaussian state space models
run_mcmc.ssm_nlg

Bayesian Inference of non-linear state space models
gaussian_approx

Gaussian Approximation of Non-Gaussian/Non-linear State Space Model
summary.mcmc_output

Summary of MCMC object
run_mcmc.ssm_sde

Bayesian Inference of SDE
ssm_sde

Univariate state space model with continuous SDE dynamics
expand_sample

Expand the Jump Chain representation
as.data.frame.mcmc_output

Convert MCMC chain to data.frame
as_bssm

Convert KFAS Model to bssm Model
svm

Stochastic Volatility Model
run_mcmc.gaussian

Bayesian Inference of Linear-Gaussian State Space Models
run_mcmc.nongaussian

Bayesian Inference of Non-Gaussian State Space Models
ekf

(Iterated) Extended Kalman Filtering
ekf_smoother

Extended Kalman Smoothing