iAR: Irregularly Observed Autoregressive Models

Data sets and functions for implementing discrete-time autoregressive models for irregularly observed time series. The models implemented include the irregular autoregressive (iAR) model (Eyheramendy et al. (2018) <doi:10.1093/mnras/sty2487>), the complex irregular autoregressive (CiAR) model (Elorrieta et al. (2019) <doi:10.1051/0004-6361/201935560>), and the bivariate irregular autoregressive (BiAR) model (Elorrieta et al. (2021) <doi:10.1093/mnras/stab1216>). For a comprehensive description of the package and its applications, see Elorrieta et al. (2026) <doi:10.32614/RJ-2026-036>.

Version:	1.3.5
Depends:	R (≥ 3.5.0)
Imports:	Rcpp (≥ 1.0.7), ggplot2, stats, Rdpack, S7, zoo
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	arfima, knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-10-27
DOI:	10.32614/CRAN.package.iAR
Author:	Elorrieta Felipe [aut, cre], Ojeda Cesar [aut], Eyheramendy Susana [aut], Palma Wilfredo [aut]
Maintainer:	Elorrieta Felipe <felipe.elorrieta at usach.cl>
License:	GPL-2
URL:	https://felipeelorrieta.github.io/iAR-package/
NeedsCompilation:	yes
Citation:	iAR citation info
Materials:	README
CRAN checks:	iAR results

Documentation:

Reference manual:	iAR.html , iAR.pdf
Vignettes:	Getting Started with iAR (source, R code)

Downloads:

Package source:	iAR_1.3.5.tar.gz
Windows binaries:	r-devel: iAR_1.3.5.zip, r-release: iAR_1.3.5.zip, r-oldrel: iAR_1.3.5.zip
macOS binaries:	r-release (arm64): iAR_1.3.5.tgz, r-oldrel (arm64): iAR_1.3.5.tgz, r-release (x86_64): iAR_1.3.5.tgz, r-oldrel (x86_64): iAR_1.3.5.tgz
Old sources:	iAR archive

Linking:

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