The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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.
| Version: | 1.5 |
| Depends: | R (≥ 3.2.3) |
| Imports: | mvtnorm, Quandl, grDevices, graphics, stats |
| Published: | 2019-03-22 |
| DOI: | 10.32614/CRAN.package.pmhtutorial |
| Author: | Johan Dahlin |
| Maintainer: | Johan Dahlin <uni at johandahlin.com> |
| License: | GPL-2 |
| URL: | https://github.com/compops/pmh-tutorial-rpkg |
| NeedsCompilation: | no |
| Citation: | pmhtutorial citation info |
| CRAN checks: | pmhtutorial results |
| Reference manual: | pmhtutorial.pdf |
| Package source: | pmhtutorial_1.5.tar.gz |
| Windows binaries: | r-devel: pmhtutorial_1.5.zip, r-release: pmhtutorial_1.5.zip, r-oldrel: pmhtutorial_1.5.zip |
| macOS binaries: | r-release (arm64): pmhtutorial_1.5.tgz, r-oldrel (arm64): pmhtutorial_1.5.tgz, r-release (x86_64): pmhtutorial_1.5.tgz, r-oldrel (x86_64): pmhtutorial_1.5.tgz |
| Old sources: | pmhtutorial archive |
Please use the canonical form https://CRAN.R-project.org/package=pmhtutorial to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.