Abstract #300953

This is the preliminary program for the 2003 Joint Statistical Meetings in San Francisco, California. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 2-5, 2003); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

Back to main JSM 2003 Program page
JSM 2003 Abstract #300953
Activity Number: 209
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract - #300953
Title: Nonparametric Lack-of-fit Test for Heteroscedastic Regression Models
Author(s): Lan Wang*+ and Michael G. Akritas and Ingrid Van Keilegom
Companies: Pennsylvania State University and Pennsylvania State University and Universite Catholique De Louvain
Address: 209 White Course F, University Park, PA, 16802,
Keywords: lack-of-fit tests ; nonparametric regression ; heteroscedasticity ; random design ; symmetric nearest-neighbor windows
Abstract:

For the heteroscedastic nonparametric regression model, Y_{ni}= m(X_{ni})+\sigma(X_{ni})\espsilon_{ni}, we propose a new test procedure for testing that the regression function m is constant or belongs to a parametric family. An extension to multiple regression for testing against the alternative of a partial linear model is also given. The test statistic is modeled after the usual lack-of-fit statistic for constant regression in the case of replicated observations, and thus is very easy to compute. The asymptotic theory uses recent developments in the asymptotic theory for analysis of variance when the number of factor levels is large. Simulated comparisons indicate that the proposed test performs favorably in relation to competing procedures.

  • The address information is for the authors that have a + after their name.
  • Authors who are presenting talks have a * after their name.

Back to the full JSM 2003 program

JSM 2003 For information, contact meetings@amstat.org or phone (703) 684-1221. If you have questions about the Continuing Education program, please contact the Education Department.
Revised March 2003