Package: iAR 1.3.0
Elorrieta Felipe
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>).
Authors:
iAR_1.3.0.tar.gz
iAR_1.3.0.tar.gz(r-4.5-noble)iAR_1.3.0.tar.gz(r-4.4-noble)
iAR_1.3.0.tgz(r-4.4-emscripten)iAR_1.3.0.tgz(r-4.3-emscripten)
iAR.pdf |iAR.html✨
iAR/json (API)
| # Install 'iAR' in R: |
| install.packages('iAR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 21 hours agofrom:acb4e2b50f. Checks:3 OK. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 10 2025 |
| R-4.5-linux-x86_64 | OK | Mar 10 2025 |
| R-4.4-linux-x86_64 | OK | Mar 10 2025 |
Exports:BiARCiARfitfoldlcforecastgentimeharmonicfitiARiARPermutationiARTestinterpolationkalmanloglikmultidatapairingitsplotplot_fitplot_forecastsimsummaryunidatautilities
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6rbibutilsRColorBrewerRcppRcppArmadilloRdpackrlangS7scalestibbleutf8vctrsviridisLitewithrzoo
