Changepoint Detection in the Presence of Outliers-Reference-Cited by-同舟云学术

Changepoint Detection in the Presence of Outliers

Published:2018-06-28 Issue:525 Volume:114 Page:169-183
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Fearnhead Paul¹^ORCID,Rigaill Guillem²³

Affiliation:

1. Department of Mathematics and Statistics, Lancaster University, Lancaster, UK

2. Institute of Plant Sciences Paris-Saclay, UMR 9213/UMR1403, CNRS, INRA, Université Paris-Sud, Université d’Evry, Université Paris-Diderot, Sorbonne Paris-Cité, Paris, France

3. Laboratoire de Mathématiques at Modélisation d’Evry (LaMME), Université d’Evry Val d’Essonne, UMR CNRS 8071, ENSIIE, USC INRA, Paris, France

Funder

Engineering and Physical Sciences Research Council

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2017.1385466

Reference42 articles.

1. Bagci, I. E. (2016), “Novel Security Mechanisms for Wireless Sensor Networks,” PhD dissertation, Lancaster University, Lancaster, UK.

2. Bagci, I. E., Roedig, U., Martinovic, I., Schulz, M., and Hollick, M. (2015), “Using Channel State Information for Tamper Detection in the Internet of Things,” in Proceedings of the 31st Annual Computer Security Applications Conference, pp. 131–140.

3. Estimating Multiple Breaks One at a Time

4. Baranowski, R., Chen, Y., and Fryzlewicz, P. (2016), “Narrowest-Over-Threshold Detection of Multiple Change-Points and Change-Point-Like Features,” arXiv:1609.00293.

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