Backfitting applies the full dataset to a model built from a smaller sample. The resulting model retains its original structure. The purpose of backfitting is to allow a model's internal distributions to accurately reflect the full data, while maintaining the model's error estimate.

Modifying equipment to make changes or add features that have been included in later models, often done for energy conservation reasons. Also called retrofitting.