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Random Operators and Stochastic Equations

Editor-in-Chief: Girko, Vyacheslav

Managing Editor: Molchanov, S.

Editorial Board: Accardi, L. / Albeverio, Sergio / Carmona, R. / Casati, G. / Christopeit, N. / Domanski, C. / Drygas, Hilmar / Gupta, A.K. / Ibragimov, I. / Kirsch, Werner / Klein, A. / Kondratyev, Yuri / Kurotschka, V. / Leonenko, N. / Loubaton, Philippe / Orsingher, E. / Pastur, L. / Rodrigues, Waldyr A. / Shiryaev, Albert / Turbin, A.F. / Veretennikov, Alexandre


CiteScore 2017: 0.32

SCImago Journal Rank (SJR) 2017: 0.177
Source Normalized Impact per Paper (SNIP) 2017: 0.592

Mathematical Citation Quotient (MCQ) 2017: 0.12

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1569-397X
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Volume 26, Issue 1

Issues

Detecting changes in linear regression models with skew normal errors

Khamis K. Said / Wei Ning
  • Corresponding author
  • Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, Ohio, USA
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  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Yubin Tian
Published Online: 2018-01-23 | DOI: https://doi.org/10.1515/rose-2018-0001

Abstract

In this article, we discuss a linear regression change-point model with skew normal errors. We propose a testing procedure, based on a modified version of the Schwarz information criterion, which is named the modified information criterion (MIC) to locate change points in such a linear regression model. Due to the difficulty of derivation of the asymptotic null distribution of the associated test statistic analytically, the empirical critical values at different significance levels are approximated through simulations. Simulations have also been conducted under different changes among parameters of interest with various sample sizes to investigate the performance of the proposed test. Such a procedure has been applied on a NASA data to illustrate the detecting process.

Keywords: Change point detection; skew normal distribution; Schwarz information criterion; linear regression model

MSC 2010: 62F03; 62J05

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About the article


Received: 2017-04-14

Accepted: 2017-12-08

Published Online: 2018-01-23

Published in Print: 2018-03-01


Citation Information: Random Operators and Stochastic Equations, Volume 26, Issue 1, Pages 1–10, ISSN (Online) 1569-397X, ISSN (Print) 0926-6364, DOI: https://doi.org/10.1515/rose-2018-0001.

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