I had to consult many references to really understand ARIMA. These are listed below.
Main Text: Forte, R. M. (2015). Mastering Predictive Analytics with R. Packt Publishing. ISBN-13: 978-1783982806, ISBN-10: 1783982802.
Suggested: Dalinina, R. (2017). Introduction to Forecasting with ARIMA
in R. https://blogs.oracle.com/ai-and-datascience/post/introduction-to-forecasting-with-arima-in-r
Nice discussion of direct and indirect effect in relation to ACF: Rajbhoj, A. (2021, December 11). ARIMA Simplified. Towards Data Science. Medium.
https://towardsdatascience.com/arima-simplified-b63315f27cbc
Fantastic intuition on MA processes: Sosna, M. (2021). A Deep Dive on ARIMA Models. https://mattsosna.com/ARIMA-deep-dive/#ma-moving-average Very good on the technical details of how exponential smoothing relates to ARIMA:
Nau, R. Introduction to ARIMA Models. Fuqua School of Business. https://people.duke.edu/~rnau/411arim.htm
Other stuff: Ariton, L. (2021, December 27). A Thorough Introduction to ARIMA Models. Analytics Vidhya – Medium.
https://medium.com/analytics-vidhya/a-thorough-introduction-to-arima-models-987a24e9ff71
Other stuff #2: Li, R. (2024, February 7). Prediction: Time Series Forecasting vs Regression. Richard Li – Medium.
https://medium.com/@rdli/prediction-time-series-forecasting-vs-regression-b4ce3159b3f2
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