Inference for multiple change points in time series via likelihood ratio scan statistics
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Cited by:
- Cho, Haeran & Kirch, Claudia, 2024. "Data segmentation algorithms: Univariate mean change and beyond," Econometrics and Statistics, Elsevier, vol. 30(C), pages 76-95.
- Haeran Cho & Claudia Kirch, 2022. "Two-stage data segmentation permitting multiscale change points, heavy tails and dependence," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 653-684, August.
- Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2022. "Modelling the COVID‐19 infection trajectory: A piecewise linear quantile trend model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1589-1607, November.
- Youssef Salman & Joseph Ngatchou-Wandji & Zaher Khraibani, 2024. "Testing a Class of Piece-Wise CHARN Models with Application to Change-Point Study," Mathematics, MDPI, vol. 12(13), pages 1-40, July.
- Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
- Cho, Haeran & Fryzlewicz, Piotr, 2023. "Multiple change point detection under serial dependence: wild contrast maximisation and gappy Schwarz algorithm," LSE Research Online Documents on Economics 120085, London School of Economics and Political Science, LSE Library.
- Lajos Horvath & Lorenzo Trapani, 2021. "Changepoint detection in random coefficient autoregressive models," Papers 2104.13440, arXiv.org.
- Cho, Haeran & Kirch, Claudia, 2022. "Bootstrap confidence intervals for multiple change points based on moving sum procedures," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
- Lijing Ma & Andrew J. Grant & Georgy Sofronov, 2020. "Multiple change point detection and validation in autoregressive time series data," Statistical Papers, Springer, vol. 61(4), pages 1507-1528, August.
- Zifeng Zhao & Feiyu Jiang & Xiaofeng Shao, 2022. "Segmenting time series via self‐normalisation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1699-1725, November.
- Ardia, David & Dufays, Arnaud & Ordás Criado, Carlos, 2023. "Linking Frequentist and Bayesian Change-Point Methods," MPRA Paper 119486, University Library of Munich, Germany.
- Chen, Zhanshou & Xu, Qiongyao & Li, Huini, 2019. "Inference for multiple change points in heavy-tailed time series via rank likelihood ratio scan statistics," Economics Letters, Elsevier, vol. 179(C), pages 53-56.
- Ji-Eun Choi & Dong Wan Shin, 2021. "A self-normalization break test for correlation matrix," Statistical Papers, Springer, vol. 62(5), pages 2333-2353, October.
- Yunwei Cui & Rongning Wu & Qi Zheng, 2021. "Estimation of change‐point for a class of count time series models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(4), pages 1277-1313, December.
- Holger Dette & Theresa Eckle & Mathias Vetter, 2020. "Multiscale change point detection for dependent data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1243-1274, December.
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