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Empirical likelihood method for segmented linear regression

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Date Issued:
2011
Summary:
For a segmented regression system with an unknown change-point over two domains of a predictor, a new empirical likelihood ratio test statistic is proposed to test the null hypothesis of no change. The proposed method is a non-parametric method which releases the assumption of the error distribution. Under the null hypothesis of no change, the proposed test statistic is shown empirically Gumbel distributed with robust location and scale parameters under various parameter settings and error distributions. Under the alternative hypothesis with a change-point, the comparisons with two other methods (Chen's SIC method and Muggeo's SEG method) show that the proposed method performs better when the slope change is small. A power analysis is conducted to illustrate the performance of the test. The proposed method is also applied to analyze two real datasets: the plasma osmolality dataset and the gasoline price dataset.
Title: Empirical likelihood method for segmented linear regression.
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Name(s): Liu, Zhihua.
Charles E. Schmidt College of Science
Department of Mathematical Sciences
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: multipart monograph
Date Issued: 2011
Publisher: Florida Atlantic University
Physical Form: electronic
Extent: ix, 42 p. : ill. (some col.)
Language(s): English
Summary: For a segmented regression system with an unknown change-point over two domains of a predictor, a new empirical likelihood ratio test statistic is proposed to test the null hypothesis of no change. The proposed method is a non-parametric method which releases the assumption of the error distribution. Under the null hypothesis of no change, the proposed test statistic is shown empirically Gumbel distributed with robust location and scale parameters under various parameter settings and error distributions. Under the alternative hypothesis with a change-point, the comparisons with two other methods (Chen's SIC method and Muggeo's SEG method) show that the proposed method performs better when the slope change is small. A power analysis is conducted to illustrate the performance of the test. The proposed method is also applied to analyze two real datasets: the plasma osmolality dataset and the gasoline price dataset.
Identifier: 774397296 (oclc), 3332719 (digitool), FADT3332719 (IID), fau:3787 (fedora)
Note(s): by Zhihua Liu.
Thesis (Ph.D.)--Florida Atlantic University, 2011.
Includes bibliography.
Electronic reproduction. Boca Raton, Fla., 200?. Mode of access: World Wide Web.
Subject(s): Change-point problems
Regression analysis
Econometrics
Limit theory (Probability theory)
Persistent Link to This Record: http://purl.flvc.org/FAU/3332719
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU