WAIC stands for the widely applicable information criterion (or Watanabe-Akaike information criterion). It is used for model selection, particularly in Bayesian settings. A smaller WAIC implies that a model should have lower predictive error.
The widely applicable information criterion (or Watanabe-Akaike information criterion) is a criterion for model selection, particularly in Bayesian settings.