Application of an "ARIMA" model to forecast milk production in Brown Swiss cows from the Peruvian highlands

Abstract

The aim of this study was to apply an ARIMA model to forecast milk production in Brown Swiss cows from the Peruvian highlands, taking data from the Chuquibambilla Research and Production Center herd of the National University of the Altiplano, Puno for the years 2008-2016 ordered by months. The data were imported into the RStudio program applying an ARIMA model that consisted of making a horizontal plot of milk production by years, a seasonal graph distributed by months and the forecasts using the commands “meanf”, “naive”, “snaive” and “rfw” both textually and graphically, to finally apply the ARIMA (1,0,0) (2,0,0) autoregressive model. It is shown that milk production is not stationary according to the Dickey Fuller test (p=0.02811). In this sense, it was classified as a non-stationary time series with a seasonal behavior related to the climatic characteristics of the highlands (rainy, transition and dry seasons). Among the forecasting models, the “seasonal naive” was more consistent with this characteristic. The forecast of the ARIMA model shows the forecast production for the year 2017 with confidence intervals at 80 and 95 %. In conclusion, the ARIMA model proposed for milk production was adequate because it allowed forecasting the productions of the year 2017.