iAR: Irregularly Observed Autoregressive Models

Data sets, functions and scripts with examples to implement autoregressive models for irregularly observed time series. The models available in this package are the irregular autoregressive model (Eyheramendy et al.(2018) <doi:10.1093/mnras/sty2487>), the complex irregular autoregressive model (Elorrieta et al.(2019) <doi:10.1051/0004-6361/201935560>) and the bivariate irregular autoregressive model (Elorrieta et al.(2021) <doi:10.1093/mnras/stab1216>).

Version: 1.2.0
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.7), ggplot2, stats, Rdpack
LinkingTo: Rcpp, RcppArmadillo
Suggests: arfima
Published: 2022-11-24
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://github.com/felipeelorrieta
NeedsCompilation: yes
CRAN checks: iAR results


Reference manual: iAR.pdf


Package source: iAR_1.2.0.tar.gz
Windows binaries: r-devel: iAR_1.2.0.zip, r-release: iAR_1.2.0.zip, r-oldrel: iAR_1.2.0.zip
macOS binaries: r-release (arm64): iAR_1.2.0.tgz, r-oldrel (arm64): iAR_1.2.0.tgz, r-release (x86_64): iAR_1.2.0.tgz, r-oldrel (x86_64): iAR_1.2.0.tgz
Old sources: iAR archive


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