Package: pmhtutorial 1.5
Johan Dahlin
pmhtutorial: Minimal Working Examples for Particle Metropolis-Hastings
Routines for state estimate in a linear Gaussian state space model and a simple stochastic volatility model using particle filtering. Parameter inference is also carried out in these models using the particle Metropolis-Hastings algorithm that includes the particle filter to provided an unbiased estimator of the likelihood. This package is a collection of minimal working examples of these algorithms and is only meant for educational use and as a start for learning to them on your own.
Authors:
pmhtutorial_1.5.tar.gz
pmhtutorial_1.5.tar.gz(r-4.5-noble)pmhtutorial_1.5.tar.gz(r-4.4-noble)
pmhtutorial_1.5.tgz(r-4.4-emscripten)pmhtutorial_1.5.tgz(r-4.3-emscripten)
pmhtutorial.pdf |pmhtutorial.html✨
pmhtutorial/json (API)
| # Install 'pmhtutorial' in R: |
| install.packages('pmhtutorial', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/compops/pmh-tutorial-rpkg/issues
Last updated 6 years agofrom:9ecfd98b27. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 13 2024 |
| R-4.5-linux | OK | Dec 13 2024 |
Exports:example1_lgssexample2_lgssexample3_svexample4_svexample5_svgenerateDatakalmanFiltermakePlotsParticleMetropolisHastingsSVModelparticleFilterparticleFilterSVmodelparticleMetropolisHastingsparticleMetropolisHastingsSVmodelparticleMetropolisHastingsSVmodelReparameterised
Dependencies:askpasscurlhttrjsonlitelatticemimemvtnormopensslQuandlR6sysxtszoo
