iAR: Irregularly Observed Autoregressive Models (original) (raw)
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 |
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