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Metrika

, Volume 81, Issue 6, pp 689–720 | Cite as

Test by adaptive LASSO quantile method for real-time detection of a change-point

  • Gabriela Ciuperca
Article

Abstract

This article proposes a test statistic based on the adaptive LASSO quantile method to detect in real-time a change in a linear model. The model can have a large number of explanatory variables and the errors don’t satisfy the classical assumptions for a statistical model. For the proposed test statistic, the asymptotic distribution under \(H_0\) is obtained and the divergence under \(H_1\) is shown. It is shown via Monte Carlo simulations, in terms of empirical sizes, of empirical powers and of stopping time detection, that the useful test statistic for applications is better than other test statistics proposed in literature. Two applications on the air pollution and in the health field data are also considered.

Keywords

Real-time detection Adaptive LASSO Quantile Asymptotic behavior 

Mathematics Subject Classification

62F05 62F35 

Notes

Acknowledgements

The author sincerely thanks the two anonymous referees, the Editor and the Associate Editor for their valuable comments which improved the quality of the paper.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.CNRS, UMR 5208, Institut Camille JordanUniversité de Lyon, Université Lyon 1Villeurbanne CedexFrance

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