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Bayesian Inference of Non-Linear and Non-Gaussian State Space Models

Vignettes

- bssm: Bayesian Inference of Non-linear and Non-Gaussian State Space Models in R"
- Diffusion models with bssm"
- Non-linear models with bssm"
- $\\psi$-APF for non-linear Gaussian state space models"

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**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 chain to data.frame**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**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**exchange:**Pound/Dollar daily exchange rates**expand_sample:**Expand the Jump Chain representation**gaussian_approx:**Gaussian Approximation of Non-Gaussian/Non-linear State Space...**importance_sample:**Importance Sampling from non-Gaussian State Space Model**kfilter:**Kalman Filtering**logLik:**Log-likelihood of a Gaussian State Space Model**logLik.nongaussian:**Log-likelihood of a Non-Gaussian State Space Model**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**nlg_example_models:**Example C++ Codes for Non-Linear Models**particle_smoother:**Particle Smoothing**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**priors:**Prior objects for bssm models**run_mcmc:**Bayesian Inference of State Space Models**run_mcmc_g:**Bayesian Inference of Linear-Gaussian State Space Models**run_mcmc_ng:**Bayesian Inference of Non-Gaussian State Space Models**run_mcmc.ssm_nlg:**Bayesian Inference of non-linear state space models**run_mcmc.ssm_sde:**Bayesian Inference of SDE**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 of MCMC object**svm:**Stochastic Volatility Model**ukf:**Unscented Kalman Filtering**Browse all...**

```
library("testthat")
test_check("bssm")
```

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