Time Series and Forecasting: Brief History and Future Research

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Data-driven prognostic method based on Bayesian approaches for direct remaining useful life prediction (2014, unknown): “Different regression models have been proposed in the literature to deal with data-driven RUL prediction problem such as the auto regressive model and the multivariate adaptive regression splines (Box and Jenkins 1976; Lewis 1992; Tsay 2000; Wu et al. 2007; Yan et al. 2004; Lee et al. 2006).”
Forecasting of demand using ARIMA model (2018, background): “Forecasting is the operation of making assumption about the future values of studied variables.(18) In manufacturing, forecasting demands is among the most crucial issues in inventory management(19); it can be used in various operational planning activities during the production process: capacity pl”
25 years of time series forecasting (2006, methodology): “Outside the IJF, good reviews on the past and future of time series methods are given by Dekimpe & Hanssens (2000) in marketing, and by Tsay (2000) in statistics.”