Stationarity Check: Ensure that the time series is stationary by examining plots and statistical tests. Parameter Identification: Determine the values of p, d, and q using techniques like the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF). Model Estimation: Fit the ARIMA model to the data using statistical software. Model Diagnostics: Check the residuals of the model to ensure that they resemble white noise. Forecasting: Use the fitted model to make future predictions.
