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betaARMA: Beta Autoregressive Moving Average Models
Fits Beta Autoregressive Moving Average (BARMA) models for time series data distributed in the standard unit interval (0, 1). The estimation is performed via the conditional maximum likelihood method using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton algorithm. The package includes tools for model fitting, diagnostic checking, and forecasting. Based on the work of Rocha and Cribari-Neto (2009) <doi:10.1007/s11749-008-0112-z> and the associated erratum Rocha and Cribari-Neto (2017) <doi:10.1007/s11749-017-0528-4>. The original code was developed by Fabio M. Bayer.
| Version: |
1.0.1 |
| Depends: |
R (≥ 3.5) |
| Imports: |
forecast |
| Suggests: |
knitr, xtable, here, moments, rmarkdown, tseries, lbfgs, ggplot2, foreach, zoo, dplyr, gridExtra |
| Published: |
2026-03-29 |
| DOI: |
10.32614/CRAN.package.betaARMA |
| Author: |
Everton da Costa 
[aut, cre],
Francisco Cribari-Neto
[ctb, ths]
(Theoretical foundations),
Vinicius Scher
[ctb] |
| Maintainer: |
Everton da Costa <everto.cost at gmail.com> |
| BugReports: |
https://github.com/Everton-da-Costa/betaARMA/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/Everton-da-Costa/betaARMA |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Materials: |
README, NEWS |
| In views: |
TimeSeries |
| CRAN checks: |
betaARMA results |
Documentation:
Downloads:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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