This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
|
76
|
Type:
|
Contributed
|
Date/Time:
|
Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
|
Sponsor:
|
Section on Nonparametric Statistics
|
Abstract - #308942 |
Title:
|
Asymptotically Sufficient Statistics in Nonparametric Regressions with Correlated Errors
|
Author(s):
|
Andrew Carter*+
|
Companies:
|
University of California, Santa Barbara
|
Address:
|
Dept of Statistics, Santa Barbara, CA, 93106-6110,
|
Keywords:
|
nonparametric regression ;
asymptotically sufficient statistics ;
asymptotics
|
Abstract:
|
Asymptotically sufficient statistics can provide a simplification of the inference in a problem without losing an appreciable amount of information about the parameters of interest. In a nonparametric regression where we want to estimate a smooth mean function in the presence of correlated noise, there are asymptotically sufficient statistics with a smaller dimension than the original observations that may also have a simplified covariance structure. We consider two possible types of correlation: short-range correlation where the asymptotically sufficient statistics are nearly uncorrelated, and long-range correlation where the covariance structure persists in the approximation. In either case, these sufficient statistics can be used to compare the nonparametric regression experiments to continuous Gaussian process experiments.
|
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 2010 program
|
2010 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.