Predictive Time Series Modeling

Tsung-wu Ho
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Tsung-wu Ho: National Taiwan Normal University

Chapter Chapter 2 in Time Series Forecasting using Machine Learning, 2025, pp 19-57 from Springer

Abstract: Abstract This chapter shows the ways to implement statistical prediction. The starting point for statistical time series forecasting is ARIMA, we introduce the automatic order selection function auto.arima(), a routine offered by package forecast. Besides ARIMA, this chapter also includes several nonlinear time series models, for example, self-exciting threshold autoregression. We also detail the procedure to generate multistep forecasts and onestep ahead forecast.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-97946-0_2

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DOI: 10.1007/978-3-031-97946-0_2

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