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Official Journal of the Asia Oceania Geosciences Society (AOGS)

Geoscience Letters Cover Image

Table 4 Univariate time series forecasting methods of this study (part 1): stochastic methods

From: One-step ahead forecasting of geophysical processes within a purely statistical framework

s/n Abbreviated name Category R algorithm(s) Implementation notes
1 Naïve Simple   
2 RW rwf {forecast} drift = TRUE
3 ARIMA_f AutoRegressive Integrated Moving Average (ARIMA) Arima {forecast}, forecast {forecast} Arima {forecast}: include.mean = TRUE, include.drift = FALSE, method = ”ML”
4 ARIMA_s Arima {forecast}, simulate {stats}
5 auto_ARIMA_f auto.arima {forecast}, forecast {forecast}  
6 auto_ARIMA_s auto.arima {forecast}, simulate {stats}  
7 auto_ARFIMA AutoRegressive Fractionally Integrated Moving Average (ARFIMA) arfima {forecast}, forecast {forecast} arfima {forecast}: estim = ”mle”
8 BATS State space bats {forecast}, forecast {forecast}  
9 ETS_s ets {forecast}, simulate {stats}  
10 SES Exponential smoothing ses {forecast}  
11 Theta thetaf {forecast}