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asa.stat.comp.06


ASA Competition: Statistical Computing Section

Session Slot: 10:30-12:20 Wednesday

Estimated Audience Size: 100

AudioVisual Request: None


Session Title: Smoothing Methods and Data Analysis

Theme Session: No

Applied Session: Yes


Session Organizer: O'Connell, Michael Becton Dickinson


Address: Becton Dickinson Research Center Research Triangle Park, NC 27709-201

Phone: 919-990-2136

Fax:

Email: Michael_A_OConnell@bdits.bd.com


Session Timing: 110 minutes total (Sorry about format):

TBA (110 minutes total) Opening Remarks by Chair - 5 or 0 minutes First Speaker - 30 minutes (or 25) Second Speaker - 30 minutes Third Speaker - 30 minutes Discussant - 10 minutes (or none) Floor Discusion - 10 minutes (or 5 or 15)


Session Chair: O'Connell, Michael Becton Dickinson


Address: Becton Dickinson Research Center Research Triangle Park, NC 27709-201

Phone: 919-990-2136

Fax:

Email: Michael_A_OConnell@bdits.bd.com


1. When is a Feature Really There? The SiZer Approach

Marron, J.S.,   University of North Carolina


Address: Department of Statistics University of North Carolina Chapel Hill, NC 27599-3260

Phone: 919-962-2188

Fax: 919-962-1279

Email: marron@stat.unc.edu

Chaudhuri, Probal, Indian Statistical Institute

Abstract: When applying smoothing methods to data, the central question is often ``which observed features are part of the true underlying curve, and which are spurious sampling artifacts?'' An answer is provided using a scale space viewpoint, where one considers the entire family of smooths indexed by the bandwidth. Different bandwidths represent different ``levels of resolution of the data''. Significance of features that are characterized by Zero crossings of the derivative (such as bumps) is easily understood, assessed and presented, simultaneously over all resolutions, via a color map in scale space.


2. FUNFITS: Fitting Functions to Data

Nychka, Douglas,   National Center for Atmospheric Research and North Carolina State University


Address: Geophysical Statistics Project National Center for Atmospheric Research Climate and Global Dynamics Division Boulder, CO 80307

Phone: 303-497-1711

Fax: 303-497-1333

Email: nychka@ucar.edu

Abstract: FUNFITS is a suite of functions that enhance the S-PLUS statistical package and facilitate curve and surface fitting. This software grew up as a project to augment S-PLUS with additional nonparametric fitting strategies. Part of this effort was to focus on three areas rich in applications of function estimation and inference: spatial statistics, response surface methodology and nonlinear time series/dynamical systems. This activity has also lead to methods for space filling designs, appropriate when the response is expected to be a complex surface. One unique feature of FUNFITS is the integration of thin plate spline methodology with the more general estimators based on spatial processes. This functionality is implemented completely in the S language and so the algorithms and source code are easily accessible. The core methods implemented in FUNFITS are object driven, including prediction, plot and summary functions that help the user interpret results and visualize the estimate.


3. Some Applications of Spline Smoothing

Gu, Chong,   National Institute of Statistical Sciences


Address: National Institute of Statistical Sciences PO Box 14006 Research Triangle Park, NC 27709-4006

Phone: 919-685-9323

Fax: 919-685-9310

Email: gu@hp6.niss.org

Abstract: Nonparametric function estimation procedures are important tools in modern data analysis, of which spline smoothing is among the more effective ones available, especially for multivariate problems. In this talk, we will present some recent developments of spline smoothing in regression, density estimation, and conditional density estimation, and illustrate their applications in data analysis.

List of speakers who are nonmembers: None


next up previous index
Next: ASA Statistical Consulting (3) Up: ASA Statistical Computing (5 Previous: asa.stat.comp.05
David Scott
6/1/1998