Beta regression for time series analysis of bounded data, with application to Canada Google Flu Trends.
Anno:
2014
Tipologia prodotto:
Articolo in Rivista
Tipologia ANVUR:
Articolo su rivista
Lingua:
Inglese
Formato:
Elettronico
Referee:
Sì
Nome rivista:
THE ANNALS OF APPLIED STATISTICS
ISSN Rivista:
1932-6157
N° Volume:
8
Numero o Fascicolo:
1
Intervallo pagine:
74-88
Parole chiave:
Beta regression; bounded time series; Gaussian copula; Google Flu Trends; surveillance
Breve descrizione dei contenuti:
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 de- pendence is modeled by a Gaussian copula, with a correlation matrix corresponding to a stationary autoregressive and moving average pro- cess. 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 es- timated by the Google Flu Trends project.
Guolo, Annamaria; Cristiano, Varin,
Beta regression for time series analysis of bounded data, with application to Canada Google Flu Trends.«THE ANNALS OF APPLIED STATISTICS»
, vol. 8
, n. 1
, 2014
, pp. 74-88