Construction of an informative hierarchical prior distribution. Application to electricity load forecasting

Tristan Launay (1, 2) , Anne Philippe (1) , Sophie Lamarche (2)

1 LMJL - Laboratoire de Mathématiques Jean Leray
2 EDF R&D - EDF R&D

n this paper, we are interested in the estimation and prediction of a parametric model on a short dataset upon which it is expected to overfit and perform badly. To overcome the lack of data (relatively to the dimension of the model) we propose the construction of a hierarchical informative Bayesian prior based upon another longer dataset which is assumed to share some similarities with the original, short dataset. We apply the methodology to a basic model for the electricity load forecasting on both simulated and real datasets, where it leads to a substantial improvement of the quality of the predictions.

Mots clés: informative prior; mcmc algorithms; small dataset; electricity load forecasting

Domaines: Statistiques [math.ST]; Théorie [stat.TH]

Tristan Launay, Anne Philippe, Sophie Lamarche. Construction of an informative hierarchical prior distribution. Application to electricity load forecasting. 2011. ⟨hal-00625117v2⟩