Robust Mean Change-Point Detecting through Laplace Linear Regression Using EM Algorithm
Author
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-11-04
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
We proposed a robust mean change-point estimation algorithm in linear regression with the assumption that the errors follow the Laplace distribution.
By representing the Laplace distribution as an appropriate scale mixture ofnormal distribution, we developed the expectation maximization (EM) algorithm to estimate the position of mean change-point.
We investigated the performance of the algorithm through different simulations, finding that our methods is robust to the distributions of errors and is effective to estimate the position of mean change-point.
Finally, we applied our method to the classical Holbert data and detected a change-point.
American Psychological Association (APA)
Yang, Fengkai. 2014. Robust Mean Change-Point Detecting through Laplace Linear Regression Using EM Algorithm. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1039790
Modern Language Association (MLA)
Yang, Fengkai. Robust Mean Change-Point Detecting through Laplace Linear Regression Using EM Algorithm. Journal of Applied Mathematics No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1039790
American Medical Association (AMA)
Yang, Fengkai. Robust Mean Change-Point Detecting through Laplace Linear Regression Using EM Algorithm. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1039790
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1039790