Package: bssm 2.0.2
bssm: Bayesian Inference of Non-Linear and Non-Gaussian State Space Models
Efficient methods for Bayesian inference of state space models via Markov chain Monte Carlo (MCMC) based on parallel importance sampling type weighted estimators (Vihola, Helske, and Franks, 2020, <doi:10.1111/sjos.12492>), particle MCMC, and its delayed acceptance version. Gaussian, Poisson, binomial, negative binomial, and Gamma observation densities and basic stochastic volatility models with linear-Gaussian state dynamics, as well as general non-linear Gaussian models and discretised diffusion models are supported. See Helske and Vihola (2021, <doi:10.32614/RJ-2021-103>) for details.
Authors:
bssm_2.0.2.tar.gz
bssm_2.0.2.tar.gz(r-4.5-noble)bssm_2.0.2.tar.gz(r-4.4-noble)
bssm_2.0.2.tgz(r-4.4-emscripten)bssm_2.0.2.tgz(r-4.3-emscripten)
bssm.pdf |bssm.html✨
bssm/json (API)
NEWS
# Install 'bssm' in R: |
install.packages('bssm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/helske/bssm/issues
- drownings - Deaths by drowning in Finland in 1969-2019
- exchange - Pound/Dollar daily exchange rates
- negbin_model - Estimated Negative Binomial Model of Helske and Vihola
- negbin_series - Simulated Negative Binomial Time Series Data
- poisson_series - Simulated Poisson Time Series Data
Last updated 1 years agofrom:7b7b8acf4e. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 02 2024 |
R-4.5-linux-x86_64 | OK | Dec 02 2024 |
Exports:ar1_lgar1_ngas_bssmas_drawsas_draws_dfasymptotic_varbootstrap_filterbsm_lgbsm_ngcheck_diagnosticscpp_example_modelekfekf_fast_smootherekf_smootherekpf_filterestimate_essexpand_samplefast_smoothergammagamma_priorgaussian_approxhalfnormalhalfnormal_prioriactimportance_samplekfilternormalnormal_priorparticle_smootherpost_correctrun_mcmcsim_smoothersmootherssm_mlgssm_mngssm_nlgssm_sdessm_ulgssm_ungsuggest_Nsvmtnormaltnormal_priorukfuniformuniform_prior
Dependencies:abindbackportsbayesplotcheckmateclicodacolorspacecpp11diagisdistributionaldplyrfansifarvergenericsggplot2ggridgesgluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgconfigplyrposteriorpurrrR6ramcmcRColorBrewerRcppRcppArmadilloreshape2rlangscalessitmostringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr
$\psi$-APF for non-linear Gaussian state space models
Rendered frompsi_pf.Rmd
usingknitr::rmarkdown
on Dec 02 2024.Last update: 2023-10-27
Started: 2020-06-09
bssm: Bayesian Inference of Non-linear and Non-Gaussian State Space Models in R
Rendered frombssm.Rmd
usingknitr::rmarkdown
on Dec 02 2024.Last update: 2023-10-27
Started: 2017-06-25
Diffusion models with bssm
Rendered fromsde_model.Rmd
usingknitr::rmarkdown
on Dec 02 2024.Last update: 2023-10-27
Started: 2021-02-22
Non-linear models with bssm
Rendered fromgrowth_model.Rmd
usingknitr::rmarkdown
on Dec 02 2024.Last update: 2023-10-27
Started: 2017-06-25