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: | 1.1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp (≥ 1.0.7), ggplot2, stats, Rdpack |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | arfima |
| Published: | 2022-07-11 |
| 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_1.1.0.tar.gz |
| Windows binaries: | r-devel: iAR_1.1.0.zip, r-release: iAR_1.1.0.zip, r-oldrel: iAR_1.1.0.zip |
| macOS binaries: | r-release (arm64): iAR_1.1.0.tgz, r-oldrel (arm64): iAR_1.1.0.tgz, r-release (x86_64): iAR_1.1.0.tgz, r-oldrel (x86_64): iAR_1.1.0.tgz |
| Old sources: | iAR archive |
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