Department of Statistical Science
Duke University
presents:
CHONG GU
gu@niss.rti.org
NISS - Research Triangle Park, NC
"Model Indexing and Smoothing Parameter Selection in Nonparametric Function Estimation"
Abstract: Smoothing parameter selection is among the most intensively studied subjects in nonparametric function estimation. A closely related issue, that of identifying a proper index for the smoothing parameter, is however largely neglected in the existing literature. Through heuristic arguments and simple simulations, we shall illustrate that most current working indices are conceptually ``incorrect'', in the sense that they are not interpretable across-replicate in repeated experiments, and as a consequence, a few popular working concepts, such as the expected mean square error and the ``degrees of freedom'', appear vulnerable under close scrutiny. The development stems from an attempt to understand the well-publicized negative correlation between optimal and cross-validation smoothing parameters, which however turns out to bear little statistical relevance.
October 24, 1997
4:00 pm - 5:00 pm
116 Old Chem Building Any questions concerning the seminar may be addressed to Cheryl McGhee @ [919] 684-8029 or e-mail cheryl@stat.duke.edu. Please contact the author(s) directly for reprints etc.