Comparative Assessment of AR, MA and ARMA for the Time Series Forecasting of Assam and Meghalaya Rainfall Division

Weather Forecasting is a serious issue in agriculture, especially in Assam and Meghalaya. The productivity of agriculture is dependent on rainfall. This paper forwards a comparative assessment of Auto-Regressive, Moving Average, and Auto-Regressive Moving Average Model for rainfall in Assam and Meghalaya. A total of 117 years of rainfall data of Assam and Meghalaya division is collected from data.gov.in [11]. The models are implemented by visualizing the time series components of rainfall. The necessary investigations such as ACF, PACF, rolling mean, and ducky fuller tests are reported in the paper for the analysis of stationarity of time series. The evaluating parameters such regression score (0.73), mean absolute error (75.70), median absolute error (61.43), mean squared error (9396.09), mand root mean square error (96.93) select the ARMA model as the best model for the time series forecasting of Assam and Meghalaya Division.