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In this paper we have compared the fit of additive models of Holt-Winters and SARIMA in time series of monthly maximum temperature in the city of Rio de Janeiro (RJ) using data from January 2003 to December 2015. The Holt-Winters additive model was chosen because the seasonal behavior of the time series. The SARIMA (1,0,1)×(1,1,1)12 was chosen because provided the best Akaike Information and Schwarz Criteria. The final model was chosen by using mean square error and mean absolute percentual error. These measures were calculated using the fitted model to the historical data. Additionally, a Diebold-Mariano test for predictive accuracy was applied and white noise characteristics of the residues were evaluated. The SARIMA (1,0,1)×(1,1,1)12 was the best model fitted and so it was adopted for maximum monthly temperature forecast for the year 2016.
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