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betaARMA

Beta Autoregressive Moving Average Models

v1.2.0 · May 23, 2026 · MIT + file LICENSE

Description

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. A ridge penalization scheme is available to improve numerical stability of the estimation, as proposed by Cribari-Neto, Costa and Fonseca (2025) <doi:10.1214/25-BJPS645>. The package includes tools for model fitting, diagnostic checking, and forecasting, along with two hydro-environmental datasets from Brazil. 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.

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OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE May 11, 2026
WARNING 12 OK · 0 NOTE · 1 WARNING · 0 ERROR · 0 FAILURE May 10, 2026
WARNING r-devel-linux-x86_64-debian-gcc

PDF version of manual

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Dependency Network

Dependencies Reverse dependencies forecast ggplot2 rlang gridExtra betaARMA

Version History

3 tracked
updated 1.2.0 ← 1.1.0 diff May 23, 2026
updated 1.1.0 ← 1.0.1 diff Apr 15, 2026
new 1.0.1 Mar 29, 2026