For FRF based model updating procedures, the selection of updating frequencies and the choice of a damping approach are important factors to obtain reliable updating resuns. This paper discusses the selection of the updating frequencies and shows that damping approaches like proportional, structural or modal damping are not satisfactory for model updating purposes.

The Winter Simulation Conference serves as the initial publication venue for many advances in ranking and selection (R&S), including the recently-developed R&S procedures that exploit high-performance parallel computing. We formulate a new stylized model for representing parallel R&S procedures, and we provide an overview of existing R&S procedures under the stylized model. We also discuss why ...

Given a finite family of functions, the goal of model selection aggregation is to construct a procedure that mimics the function from this family that is the closest to an unknown regression function. More precisely, we consider a general regression model with fixed design and measure the distance between functions by the mean squared error at the design points. While procedures based on expone...

This paper describes a unifying framework for five highly influential but disparate theories of natural learning and behavioral action selection. These theories are normally considered independently, with their own experimental procedures and results. The framework presented builds on a structure of connection types, propagation rules and learning rules, which are used in combination to integra...

Statistical procedures for variable selection have become integral elements in any analysis. Successful procedures are characterized by high predictive accuracy, yielding interpretable models while retaining computational efficiency. Penalized methods that perform coefficient shrinkage have been shown to be successful in many cases. Models with correlated predictors are particularly challenging...

OBJECTIVES In epidemiological studies, it is important to identify independent associations between collective exposures and a health outcome. The current stepwise selection technique ignores stochastic errors and suffers from a lack of stability. The alternative LASSO-penalized regression model can be applied to detect significant predictors from a pool of candidate variables. However, this te...