Beta autoregressive moving average models

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Kumaraswamy autoregressive moving average models for double bounded environmental data (2017, methodology): “…similar construction as the generalized autoregressive and moving average model (GARMA) (Benjamin et al., 2003) and the beta autoregressive and moving average model (βARMA) (Rocha and Cribari-Neto, 2009), but we shall employ a parametrization for the Kumaraswamy distribution in terms of its median.”
Beta Regression in R (2010, methodology): “An additional line of research and implementation is that of dynamic beta regression models, such as the class of ARMA models proposed by Rocha and Cribari-Neto (2009) .”
Beta regression for time series analysis of bounded data, with application to Canada Google Flu Trends. (2014, methodology): “Recent developments of beta regression analysis of bounded time series have been addressed to observation-driven models [Rocha and Cribari-Neto (2009), Casarin, Dalla Valle and Leisen (2012)] and to parameter-driven models [Da-Silva and Migon (2012)].”