Fast and Scalable Algorithm for Detection of Structural Breaks in Big VAR Models
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[1] P. Fryzlewicz. Tail-greedy bottom-up data decompositions and fast multiple change-point detection , 2018, The Annals of Statistics.
[2] Piotr Fryzlewicz,et al. Multiple‐change‐point detection for high dimensional time series via sparsified binary segmentation , 2015, 1611.08639.
[3] V. Liebscher,et al. Consistencies and rates of convergence of jump-penalized least squares estimators , 2009, 0902.4838.
[4] G. Michailidis,et al. Regularized estimation in sparse high-dimensional time series models , 2013, 1311.4175.
[5] David S. Matteson,et al. A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data , 2013, 1306.4933.
[6] Alexander Aue,et al. Detecting and dating structural breaks in functional data without dimension reduction , 2015, 1511.04020.
[7] Deniz Erdogmus,et al. Decoding of multichannel EEG activity from the visual cortex in response to pseudorandom binary sequences of visual stimuli , 2011, Int. J. Imaging Syst. Technol..
[8] A. Aue,et al. Structural breaks in time series , 2013 .
[9] Ali Shojaie,et al. Joint Structural Break Detection and Parameter Estimation in High-Dimensional Nonstationary VAR Models , 2017, Journal of the American Statistical Association.
[10] George Michailidis,et al. Change point estimation in high dimensional Markov random‐field models , 2014, Journal of the Royal Statistical Society. Series B, Statistical methodology.
[11] C. Ing,et al. Threshold Estimation via Group Orthogonal Greedy Algorithm , 2017 .
[12] H. Dette,et al. Detection of Multiple Structural Breaks in Multivariate Time Series , 2013, 1309.1309.
[13] Tengyao Wang,et al. High dimensional change point estimation via sparse projection , 2016, 1606.06246.
[14] George Michailidis,et al. Regularized Estimation and Testing for High-Dimensional Multi-Block Vector-Autoregressive Models , 2017, J. Mach. Learn. Res..
[15] George Michailidis,et al. Multiple Change Points Detection in Low Rank and Sparse High Dimensional Vector Autoregressive Models , 2020, IEEE Transactions on Signal Processing.
[16] P. Fryzlewicz,et al. Multiple‐change‐point detection for auto‐regressive conditional heteroscedastic processes , 2014 .
[17] N. Chan,et al. Group LASSO for Structural Break Time Series , 2014 .
[18] Piotr Fryzlewicz,et al. Simultaneous multiple change-point and factor analysis for high-dimensional time series , 2016, Journal of Econometrics.
[19] Piotr Fryzlewicz,et al. Wild binary segmentation for multiple change-point detection , 2014, 1411.0858.
[20] Z. Harchaoui,et al. Multiple Change-Point Estimation With a Total Variation Penalty , 2010 .
[21] Haeran Cho,et al. Change-point detection in panel data via double CUSUM statistic , 2016, 1611.08631.
[22] H. Ombao,et al. SLEX Analysis of Multivariate Nonstationary Time Series , 2005 .
[23] Kam Chung Wong,et al. Lasso guarantees for $\beta$-mixing heavy-tailed time series , 2017, 1708.01505.
[24] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..
[25] R. Tibshirani,et al. Sparsity and smoothness via the fused lasso , 2005 .
[26] Venkata K. Jandhyala,et al. An Efficient Two Step Algorithm for High Dimensional Change Point Regression Models Without Grid Search , 2018, J. Mach. Learn. Res..
[27] Venkata K. Jandhyala,et al. Inference on the change point under a high dimensional sparse mean shift , 2021 .
[28] Po-Ling Loh,et al. High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity , 2011, NIPS.
[29] P. Fearnhead,et al. Optimal detection of changepoints with a linear computational cost , 2011, 1101.1438.
[30] Richard A. Davis,et al. Structural Break Estimation for Nonstationary Time Series Models , 2006 .