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
DOI: 10.32614/CRAN.package.statespacer
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:

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