|
Activity Number:
|
271
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Tuesday, August 5, 2008 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
Section on Nonparametric Statistics
|
| Abstract - #301647 |
|
Title:
|
BLUP for Functional Data
|
|
Author(s):
|
Ana Kupresanin*+
|
|
Companies:
|
Arizona State University
|
|
Address:
|
, , ,
|
|
Keywords:
|
BLUP ; Canonical correlation ; Functional data ; Reproducing kernel Hilbert space ; Stochastic process
|
|
Abstract:
|
We consider the regression setting where either the predictor or the response or both are random functions defined on a compact subset of R. We approach the regression problem from the best linear predictor point of view and our motivation comes from the fact that regression is related to canonical correlation analysis. The resulting form for the best linear unbiased predictor is derived using the isomorphism that relates a second-order process to the reproducing kernel Hilbert space generated by its covariance kernel. We implement the proposed predictor and study it through simulation.
|
- 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 2008 program |
