Bayesian model selection provides a coherent framework for comparing competing statistical models by balancing goodness of fit against model complexity through the use of prior distributions and ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

High-dimensional model selection in multivariate statistics addresses the challenge of choosing an appropriate statistical model when both the number of variables and the sample size can grow large ...