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Journal of the American Statistical Association Volume 110, 2015 - Issue 512
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Review

Self-Normalization for Time Series: A Review of Recent Developments

Xiaofeng ShaoView further author information
Pages 1797-1817 | Received 01 Sep 2014, Published online: 15 Jan 2016

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Cheuk Hin Cheng & Kin Wai Chan. (2023) A General Framework for Constructing Locally Self-Normalized Multiple-Change-Point Tests. Journal of Business & Economic Statistics 0:0, pages 1-13.
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Christina Parpoula & Alex Karagrigoriou. (2022) On optimal segmentation and parameter tuning for multiple change-point detection and inference. Journal of Statistical Computation and Simulation 92:18, pages 3789-3816.
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Matteo Barigozzi, Giuseppe Cavaliere & Lorenzo Trapani. (2022) Inference in Heavy-Tailed Nonstationary Multivariate Time Series. Journal of the American Statistical Association 0:0, pages 1-17.
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Yangfan Zhang, Runmin Wang & Xiaofeng Shao. (2022) Adaptive Inference for Change Points in High-Dimensional Data. Journal of the American Statistical Association 117:540, pages 1751-1762.
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Holger Dette & Josua Gösmann. (2020) A Likelihood Ratio Approach to Sequential Change Point Detection for a General Class of Parameters. Journal of the American Statistical Association 115:531, pages 1361-1377.
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Changrang Zhou, Ronald van Nooijen, Alla Kolechkina & Markus Hrachowitz. (2019) Comparative analysis of nonparametric change-point detectors commonly used in hydrology. Hydrological Sciences Journal 64:14, pages 1690-1710.
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Uwe Hassler & Mehdi Hosseinkouchack. (2019) Ratio tests under limiting normality. Econometric Reviews 38:7, pages 793-813.
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Yacouba Boubacar Maïnassara & Bruno Saussereau. (2018) Diagnostic Checking in Multivariate ARMA Models With Dependent Errors Using Normalized Residual Autocorrelations. Journal of the American Statistical Association 113:524, pages 1813-1827.
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Ting Zhang & Liliya Lavitas. (2018) Unsupervised Self-Normalized Change-Point Testing for Time Series. Journal of the American Statistical Association 113:522, pages 637-648.
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Yongmiao Hong, Oliver Linton, Brendan McCabe, Jiajing Sun & Shouyang Wang. (2024) Kolmogorov–Smirnov type testing for structural breaks: A new adjusted-range based self-normalization approach. Journal of Econometrics 238:2, pages 105603.
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Dylan Glotzer, Vladas Pipiras, Vadim Belenky, Kenneth M. Weems & Michael D. Levine. (2023) Statistical inference for mean and variance of oscillatory processes. Ocean Engineering 289, pages 116215.
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Jiti Gao, Bin Peng & Yayi Yan. (2023) Higher-order Expansions and Inference for Panel Data Models. Journal of the American Statistical Association, pages 1-26.
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Runmin Wang & Xiaofeng Shao. (2023) Dating the break in high-dimensional data. Bernoulli 29:4.
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Min Gao, Xiaoping Shi, Xuejun Wang & Wenzhi Yang. (2023) Combination Test for Mean Shift and Variance Change. Symmetry 15:11, pages 1975.
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Yi Zhang & Xiaofeng Shao. (2023) Another look at bandwidth-free inference: a sample splitting approach. Journal of the Royal Statistical Society Series B: Statistical Methodology.
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Karsten Reichold & Carsten Jentsch. (2023) Bootstrap Inference in Cointegrating Regressions: Traditional and Self-Normalized Test Statistics. Journal of Business & Economic Statistics, pages 1-97.
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Matei Demetrescu, Christoph Hanck & Robinson Kruse-Becher. (2023) Robust Fixed- Inference in the Presence of Time-Varying Volatility . Econometrics and Statistics.
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Y. Boubacar Maïnassara & A. Ilmi Amir. (2023) Portmanteau tests for periodic ARMA models with dependent errors. Journal of Time Series Analysis.
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Wenzhi Yang, Huanshuo Liu, Yiwei Wang & Xuejun Wang. (2022) Data-driven estimation of change-points with mean shift. Journal of the Korean Statistical Society 52:1, pages 130-153.
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Yacouba Boubacar Maïnassara, Youssef Esstafa & Bruno Saussereau. (2023) Diagnostic checking in FARIMA models with uncorrelated but non-independent error terms. Electronic Journal of Statistics 17:1.
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Feiyu Jiang, Runmin Wang & Xiaofeng Shao. (2023) Robust inference for change points in high dimension. Journal of Multivariate Analysis 193, pages 105114.
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Feiyu Jiang, Zifeng Zhao & Xiaofeng Shao. (2023) Time series analysis of COVID-19 infection curve: A change-point perspective. Journal of Econometrics 232:1, pages 1-17.
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Annika Betken & Martin Wendler. (2022) Rank-based change-point analysis for long-range dependent time series. Bernoulli 28:4.
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Zifeng Zhao, Feiyu Jiang & Xiaofeng Shao. (2022) Segmenting Time Series via Self-Normalisation. Journal of the Royal Statistical Society Series B: Statistical Methodology 84:5, pages 1699-1725.
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Uwe Hassler & Mehdi Hosseinkouchack. (2022) Joint Hypothesis Testing from Heterogeneous Samples under Cross-dependence. Econometrics and Statistics.
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Runmin Wang, Changbo Zhu, Stanislav Volgushev & Xiaofeng Shao. (2022) Inference for change points in high-dimensional data via selfnormalization. The Annals of Statistics 50:2.
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Antonella Falini, Francesca Mazzia & Cristiano Tamborrino. (2022) Spline based Hermite quasi-interpolation for univariate time series. Discrete & Continuous Dynamical Systems - S 0:0, pages 0.
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Nikolaos Passalis, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis & Anastasios Tefas. (2021) Forecasting Financial Time Series Using Robust Deep Adaptive Input Normalization. Journal of Signal Processing Systems 93:10, pages 1235-1251.
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Yacouba Boubacar Maïnassara, Youssef Esstafa & Bruno Saussereau. (2021) Estimating FARIMA models with uncorrelated but non-independent error terms. Statistical Inference for Stochastic Processes 24:3, pages 549-608.
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Florian Heinrichs & Holger Dette. (2021) A distribution free test for changes in the trend function of locally stationary processes. Electronic Journal of Statistics 15:2.
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Runmin Wang & Xiaofeng Shao. (2020) Hypothesis testing for high-dimensional time series via self-normalization. The Annals of Statistics 48:5.
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Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj & Alexandros Iosifidis. (2020) Deep Adaptive Input Normalization for Time Series Forecasting. IEEE Transactions on Neural Networks and Learning Systems 31:9, pages 3760-3765.
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Ji-Eun Choi & Dong Wan Shin. (2020) A self-normalization test for correlation change. Economics Letters 193, pages 108363.
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Holger Dette, Kevin Kokot & Stanislav Volgushev. (2020) Testing relevant hypotheses in functional time series via self-normalization. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 82:3, pages 629-660.
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Xuexin Wang & Yixiao Sun. (2020) An Asymptotic F Test for Uncorrelatedness in the Presence of Time Series Dependence . Journal of Time Series Analysis 41:4, pages 536-550.
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Ji Hyung Lee, Oliver Linton & Yoon-Jae Whang. (2019) QUANTILOGRAMS UNDER STRONG DEPENDENCE. Econometric Theory 36:3, pages 457-487.
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Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj & Alexandros Iosifidis. (2020) Adaptive Normalization for Forecasting Limit Order Book Data Using Convolutional Neural Networks. Adaptive Normalization for Forecasting Limit Order Book Data Using Convolutional Neural Networks.
Yacouba Boubacar Maïnassara & Abdoulkarim Ilmi Amir. (2019) Distribution of residual autocorrelations for multiplicative seasonal ARMA models with uncorrelated but nonindependent error terms. Statistica Neerlandica 73:4, pages 454-474.
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Ting Zhang, Liliya Lavitas & Qiao Pan. (2019) Asymptotic Behavior of Optimal Weighting in Generalized Self‐Normalization for Time Series. Journal of Time Series Analysis 40:5, pages 831-851.
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Liliya Lavitas & Ting Zhang. (2018) A Time‐Symmetric Self‐Normalization Approach for Inference of Time Series. Journal of Time Series Analysis 39:5, pages 748-762.
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Willa W. Chen & Rohit S. Deo. (2018) Subsampling based inference for statistics under thick tails using self-normalization . Statistics & Probability Letters 138, pages 95-103.
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Cheol-Keun Cho. (2022) Self-Normalization Inference for Linear Trends in Cointegrating Regressions. SSRN Electronic Journal.
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Yongmiao Hong, Brendan McCabe, Jiajing Sun & Shouyang Wang. (2021) Testing for Structural Breaks – A New Self-Normalization Approach Based on the Adjusted Sample Range. SSRN Electronic Journal.
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Ji Hyung Lee, Oliver B. Linton & Yoon-Jae Whang. (2017) Quantilograms under Strong Dependence. SSRN Electronic Journal.
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