Bayesian model selection offers a coherent framework for identifying the most plausible models when the number of candidate predictors greatly exceeds the number of observations. Central to this ...

Information theory provides a unifying framework for both model selection and data compression by quantifying the trade-off between model complexity and the fidelity with which a model represents data ...