JSM Preliminary Online Program
This is the preliminary program for the 2006 Joint Statistical Meetings in Seattle, Washington.

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 2006 Program page

Activity Number: 420
Type: Contributed
Date/Time: Wednesday, August 9, 2006 : 10:30 AM to 12:20 PM
Sponsor: Section on Physical and Engineering Sciences
Abstract - #307421
Title: Wavelet-Based Estimation of Linear Regression Models with Two Errors: a Long Memory and a White Noise
Author(s): Kyungduk Ko*+
Companies: Boise State University
Address: 1910 University Drive, Boise, ID, 83725-1555,
Keywords: long memory ; discrete wavelet transform ; linear regression ; EM algorithm
Abstract:

Linear regression models with long memory error have been useful in many areas, such as signal and image processing, climatology, and economics. Here we analyze a linear regression model with two errors, a long memory and a white noise. Discrete wavelet transforms are applied to the explanatory and response variables in order to simplify the dense variance-covariance matrix of the additive error structure of a long memory and a white noise. An EM algorithm is then adopted for the estimation of the model parameters. Performances are evaluated on simulated and real data.

  • 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 2006 program

JSM 2006 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.
Revised April, 2006