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statespacer: State Space Modelling in 'R'

A tool that makes estimating models in state space form a breeze. See "Time Series Analysis by State Space Methods" by Durbin and Koopman (2012, ISBN: 978-0-19-964117-8) for details about the algorithms implemented.

Version: 0.5.0
Depends: R (≥ 3.6)
Imports: Rdpack, stats, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: datasets, graphics, knitr, numDeriv (≥ 2016.8-1.1), optimx (≥ 2020-4.2), rmarkdown
Published: 2023-01-27
Author: Dylan Beijers [aut, cre]
Maintainer: Dylan Beijers <dylanbeijers at gmail.com>
BugReports: https://github.com/DylanB95/statespacer/issues/
License: MIT + file LICENSE
URL: https://DylanB95.github.io/statespacer/, https://github.com/DylanB95/statespacer/
NeedsCompilation: yes
Citation: statespacer citation info
Materials: NEWS
In views: TimeSeries
CRAN checks: statespacer results

Documentation:

Reference manual: statespacer.pdf
Vignettes: Fitting ARIMA models with statespacer
Dictionary of statespacer
Introduction to statespacer
statespacer applied to UK Road Deaths
Specify it yourself!

Downloads:

Package source: statespacer_0.5.0.tar.gz
Windows binaries: r-devel: statespacer_0.5.0.zip, r-release: statespacer_0.5.0.zip, r-oldrel: statespacer_0.5.0.zip
macOS binaries: r-release (arm64): statespacer_0.5.0.tgz, r-oldrel (arm64): statespacer_0.5.0.tgz, r-release (x86_64): statespacer_0.5.0.tgz, r-oldrel (x86_64): statespacer_0.5.0.tgz
Old sources: statespacer archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=statespacer 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.
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