A1831
Title: Subdata selection or sampling methods
Authors: John Stufken - George Mason University (United States) [presenting]
Abstract: Selecting or sampling subdata from a larger dataset has received increasing attention over the past decade and many methods have been proposed. Two of these methods are examined: one model-based and one model-free. The first is based on efficient estimation of model parameters, while the second focuses on prediction. Selected strengths and weaknesses are discussed.
