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March 2014 Beta regression for time series analysis of bounded data, with application to Canada Google® Flu Trends
Annamaria Guolo, Cristiano Varin
Ann. Appl. Stat. 8(1): 74-88 (March 2014). DOI: 10.1214/13-AOAS684

Abstract

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.

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Annamaria Guolo. Cristiano Varin. "Beta regression for time series analysis of bounded data, with application to Canada Google® Flu Trends." Ann. Appl. Stat. 8 (1) 74 - 88, March 2014. https://doi.org/10.1214/13-AOAS684

Information

Published: March 2014
First available in Project Euclid: 8 April 2014

zbMATH: 06302228
MathSciNet: MR3191983
Digital Object Identifier: 10.1214/13-AOAS684

Rights: Copyright © 2014 Institute of Mathematical Statistics

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Vol.8 • No. 1 • March 2014
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