Corrections to rule-based forecasting: findings from a replication

Abstract Rule-Based Forecasting (RBF) is an expert system that combines forecasts from simple extrapolation methods based on features of time series. In this study, we provide corrections to ten of the 99 rules contained in RBF. These corrections were identified during a replication of RBF. Empirical comparisons indicate that the corrections did not lead to a noticeable improvement in accuracy when tested against some of the original data. However, in light of the fact that several studies are extending the work on RBF, it is important to report on these corrections to RBF.