“…The ARIMA methods (p, d, q), where "p" are the parameters of the lag numbers, "d" is the degree of differentiation and "q" the order of the moving average model is based on identification, estimation, diagnosis and forecasting [7,9]. Thus, ARIMA (1,0,0) indicates an autoregressive model that predicts the current data based on the previous observation; the ARIMA (0,0,1) predicts the current data based on observation and previous error and ARIMA (1,1,0) indicates an integrated autoregressive model [9]. Equation (3) depicts this latter model [10].…”