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Journal of the American Statistical Association Volume 109, 2014 - Issue 507
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Theory and Methods

Segmented Model Selection in Quantile Regression Using the Minimum Description Length Principle

Alexander Aue
,
Rex C. Y. Cheung
,
Thomas C. M. Lee
&
Ming Zhong
Pages 1241-1256 | Received 01 Apr 2013, Published online: 02 Oct 2014

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Laura Jula Vanegas, Merle Behr & Axel Munk. (2022) Multiscale Quantile Segmentation. Journal of the American Statistical Association 117:539, pages 1384-1397.
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Simon Behrendt. (2021) Structural breaks in Box-Cox transforms of realized volatility: a model selection perspective. Quantitative Finance 21:11, pages 1905-1919.
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Yi Li & Zongyi Hu. (2021) Bayesian bent line quantile regression model. Communications in Statistics - Theory and Methods 50:17, pages 3972-3987.
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Zifeng Zhao & Chun Yip Yau. (2021) Alternating Pruned Dynamic Programming for Multiple Epidemic Change-Point Estimation. Journal of Computational and Graphical Statistics 30:3, pages 808-821.
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Yunlong Wang, Zhaojun Wang & Xuemin Zi. (2020) Rank-based multiple change-point detection. Communications in Statistics - Theory and Methods 49:14, pages 3438-3454.
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Gabriela Ciuperca. (2017) Real time change-point detection in a nonlinear quantile model. Sequential Analysis 36:1, pages 87-110.
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Articles from other publishers (14)

Haeran Cho & Claudia Kirch. (2024) Data segmentation algorithms: Univariate mean change and beyond. Econometrics and Statistics 30, pages 76-95.
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Danshu Sheng & Dehui Wang. (2024) Change-points analysis for generalized integer-valued autoregressive model via minimum description length principle. Applied Mathematical Modelling 127, pages 193-216.
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Mahmoud Zarepour & Reza Habibi. (2023) A Quasi-Bayesian change point detection with exchangeable weights. Journal of Statistical Planning and Inference 222, pages 226-240.
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Zhenyu Wei, Raymond K. W. Wong & Thomas C. M. Lee. (2022) Extending the Use of MDL for High-Dimensional Problems: Variable Selection, Robust Fitting, and Additive Modeling. Extending the Use of MDL for High-Dimensional Problems: Variable Selection, Robust Fitting, and Additive Modeling.
Cong Xu & Thomas C. M. Lee. (2022) Statistical Consistency for Change Point Detection and Community Estimation in Time-Evolving Dynamic Networks. IEEE Transactions on Signal and Information Processing over Networks 8, pages 215-227.
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Suthakaran Ratnasingam & Wei Ning. (2020) Sequential change point detection for high‐dimensional data using nonconvex penalized quantile regression. Biometrical Journal 63:3, pages 575-598.
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Housen Li, Qinghai Guo & Axel Munk. (2019) Multiscale change-point segmentation: beyond step functions. Electronic Journal of Statistics 13:2.
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Feipeng Zhang & Qunhua Li. (2017) Robust bent line regression. Journal of Statistical Planning and Inference 185, pages 41-55.
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Alexander Aue, Rex C.Y. Cheung, Thomas C.M. Lee & Ming Zhong. (2017) Piecewise quantile autoregressive modeling for nonstationary time series. Bernoulli 23:1.
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Bin Xu & Boqiang Lin. (2016) A quantile regression analysis of China's provincial CO2 emissions: Where does the difference lie?. Energy Policy 98, pages 328-342.
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Lei Wang, Lingyu Xu, Jie Yu, Yunlan Xue & Gaowei Zhang. (2016) Context-aware edge similarity segmentation algorithm of time series. Cluster Computing 19:3, pages 1421-1436.
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Raymond K. W. Wong, Vinay L. Kashyap, Thomas C. M. Lee & David A. van Dyk. (2016) Detecting abrupt changes in the spectra of high-energy astrophysical sources. The Annals of Applied Statistics 10:2.
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Nooshin Omranian, Bernd Mueller-Roeber & Zoran Nikoloski. (2015) Segmentation of biological multivariate time-series data. Scientific Reports 5:1.
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Marie Hušková & Zuzana Prášková. (2014) Comments on: Extensions of some classical methods in change point analysis. TEST 23:2, pages 265-269.
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