- See: Cross-Validation, Out-of-Sample Forecasting Experiment.
- (Fomby, 2019) ⇒ Thomas B. Fomby (2019). "Out-of-Sample Forecasting Experiment" Retrieved: 2019-05-01.
- 1) Divide the available data on the target variable, [math]y_t[/math], (here we assume [math]y_t[/math] is stationary) and the proposed leading indicator,[math]x_t[/math] , (likewise we assume that [math]x_t[/math] is stationary) into two parts: the in-sample data set (roughly 80% of the data) and the out-of-sample data set (the remaining 20% of the entire data set).
- (Sammut & Webb, 2017) ⇒ Claude Sammut, and Geoffrey I. Webb. (2017). “Out-of-Sample Data.” In: (Sammut & Webb, 2011)