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.

Getting started

Package details

AuthorEverton da Costa [aut, cre] (ORCID: <https://orcid.org/0000-0001-7580-2639>), Francisco Cribari-Neto [ctb, ths] (ORCID: <https://orcid.org/0000-0002-5909-6698>, Theoretical foundations), Vinicius Scher [ctb] (ORCID: <https://orcid.org/0000-0003-0406-0265>)
MaintainerEverton da Costa <everto.cost@gmail.com>
LicenseMIT + file LICENSE
Version1.0.1
URL https://github.com/Everton-da-Costa/betaARMA
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("betaARMA")

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betaARMA documentation built on March 29, 2026, 5:08 p.m.