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Research Article Open access CC BY 4.0

Seasonal Autoregressive Integrated Moving Average (SARIMA) Model for the Analysis of Frequency of Monthly Rainfall in Osun State, Nigeria

Samuel Olorunfemi Adams, Bello Mustapha, Auta Irinew Alumbugu

Physical Science International Journal · pp. 1–9 · Published 10 Aug 2019

10.9734/psij/2019/v22i430139

Abstract

The Seasonal Autoregressive Integrated Moving Average (SARIMA) model is proposed for Osun State monthly rainfall data and the analysis was based on probability time series modeling approach. The Plot of the original data shows that the time series is stationary and the Augmented Dickey-Fuller test did not suggest otherwise. The graph further displays evidence of seasonality and it was removed by seasonal differencing. The plots of the ACF and PACF show spikes at seasonal lags respectively, suggesting SARIMA (1, 0, 1) (2, 1, 1). Though the diagnostic check on the model favoured the fitted model, the Auto Regressive parameter was found to be statistically insignificant and this led to a reduced SARIMA (1, 0, 1) (1, 1, 1)  model that best fit the data and was used to make forecast.

SARIMA model time series Dickey-Fuller test autoregressive parameter rainfall data

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