Watanabe–Akaike information criterion

Watanabe-Akaike Information Criterion, or WAIC, is a tool used to figure out which of 2 or more models is the best. It compares the models and looks at how well they fit the data (like how the lines fit the dots on a graph). WAIC examines how well the model explains the data, and it also looks at how confident we can be in the model. WAIC then figures out which model is the best one to use.