Detecting changes in mean in the presence of time‐varying autocovariance-Reference-Cited by-同舟云学术

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Detecting changes in mean in the presence of time‐varying autocovariance

Published:2021-03-29 Issue:1 Volume:10 Page:
ISSN:2049-1573
Container-title:Stat
language:en
Short-container-title:Stat

Author:

McGonigle Euan T.¹²^ORCID,Killick Rebecca³^ORCID,Nunes Matthew A.⁴^ORCID

Affiliation:

1. STOR‐i Centre for Doctoral Training Lancaster University Lancaster LA1 4YF UK

2. School of Mathematics University of Bristol Bristol BS8 1UG UK

3. Department of Mathematics and Statistics Lancaster University Lancaster LA1 4YF UK

4. Department of Mathematical Sciences University of Bath Bath BA2 7AY UK

Funder

Engineering and Physical Sciences Research Council

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sta4.351

Reference46 articles.

1. Computation and analysis of multiple structural change models

2. Baranowski R. Chen Y. &Fryzlewicz P.(2016).not: Narrowest‐over‐threshold change‐point detection. R Package Version 1.0.

3. Narrowest-over-threshold detection of multiple change points and change-point-like features

4. Dependent multiplier bootstraps for non-degenerate U-statistics under mixing conditions with applications

5. Exceptional retreat of Novaya Zemlya's marine-terminating outlet glaciers between 2000 and 2013

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1. Detecting changes in the trend function of heteroscedastic time series;Bernoulli;2024-11-01

2. Changepoint detection-assisted nonparametric clustering for unsupervised temporal sign segmentation;Engineering Applications of Artificial Intelligence;2024-01

3. Robust multiscale estimation of time-average variance for time series segmentation;Computational Statistics & Data Analysis;2023-03

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