The Annals of Applied Statistics
- Ann. Appl. Stat.
- Volume 8, Number 1 (2014), 74-88.
Beta regression for time series analysis of bounded data, with application to Canada Google® Flu Trends
Bounded time series consisting of rates or proportions are often encountered in applications. This manuscript proposes a practical approach to analyze bounded time series, through a beta regression model. The method allows the direct interpretation of the regression parameters on the original response scale, while properly accounting for the heteroskedasticity typical of bounded variables. The serial dependence is modeled by a Gaussian copula, with a correlation matrix corresponding to a stationary autoregressive and moving average process. It is shown that inference, prediction, and control can be carried out straightforwardly, with minor modifications to standard analysis of autoregressive and moving average models. The methodology is motivated by an application to the influenza-like-illness incidence estimated by the Google® Flu Trends project.
Ann. Appl. Stat. Volume 8, Number 1 (2014), 74-88.
First available in Project Euclid: 8 April 2014
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Guolo, Annamaria; Varin, Cristiano. Beta regression for time series analysis of bounded data, with application to Canada Google ® Flu Trends. Ann. Appl. Stat. 8 (2014), no. 1, 74--88. doi:10.1214/13-AOAS684. https://projecteuclid.org/euclid.aoas/1396966279
- Supplementary material: R Code. An example of R code implementing beta regression for time series analysis of Google® Flu Trends.