Abstract :
Autoregressive and Moving Average (ARIMA) which are mixture of autoregressive (AR) and moving average (MA) models are the most common stationary Box-Jenkins models. Non-stationary models which are models stationary by difference operator are called autoregressive moving average (ARIMA) models. ARIMA model are also called model with that fits to time series and forecasting. In this study, production amount of nutfruit species (pistachios, walnuts, hazelnuts, almond and chestnuts) were analyzed by Box Jenkins methodology for the years 1936–2011. After the data are stationary, Autoregressive Integrated (ARIMA(2,1,0)) pistachios production, Autoregressive Integrated (ARIMA(1,1,0)) production of walnuts, Integrated Moving Average (ARIMA(0,1,1)) production of hazelnuts and almond and Seasonal Autoregressive Integrated Moving Average models ( 9 ARIMA(0,1, 0)(0, 0,1) ) production of chestnuts were determined as the fitting model for the data. The forecast are proposed for the period 2012-2020 by using the obtained models. According to the proposed forecasts increase in nut production is expected. As a result, predictions were obtained between 2012–2020, established policies for the future of production of nuts fruit is intended to give a direction.
NaturalLanguageKeyword :
ARIMA models , Box , Jenkins technigne , Forecasting , Production of nut fruit
