ADVANCED STATISTICAL METHODS: INFERENCE, VARIABLE SELECTION, AND EXPERIMENTAL DESIGN

We provide a tutorial overview of recent advances in three methodological streams of statistical literature: design of experiments, variable selection, and approximate inference. For some of these areas (such as design of experiments), their connections to simulation research have long been known and appreciated; in other cases (such as variable selection), however, these connections are only now beginning to be built. Our presentation focuses primarily on the statistical literature, aiming to show state-of-the-art thinking with regard to these problems, but we also point out possible opportunities to use these methods in new ways for both theory and applications within simulation.