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While there is considerable work on change point analysis in univariate time series, more and more data being collected comes from high dimensional multivariate settings.
Evaluating stationarity via change-point alternatives with applications to fMRI data
J. A. D. Aston and C. Kirch · 1948
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Continuous Inspection Schemes
E. S. Page · 1954
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Convergence of probability measures
P. Billingsley · 1968
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Choosing a point from the surface of a sphere
G. Marsaglia · 1972
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Extensions of lipschitz mappings into a hilbert space
W. B. Johnson and J. Lindenstrauss · 1984
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Introduction to statistical time series
W. A. Fuller · 1996
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Limit Theorems in Change-Point Analysis
M. Csörgő and L. Horváth · 1997
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Testing for Changes in Multivariate Dependent Observations with an Application to Temperature Changes
L. Horváth, P. Kokoszka, and J. Steinebach · 1999
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Elements of Large Sample Theory
E. L. Lehmann · 1999
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Accuracy and stability of numerical algorithms
N. J. Higham · 2002
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SLEX analysis of multivariate nonstationary time series
H. Ombao, R. Von Sachs, and W. Guo · 2005
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Higher-order accurate, positive semi-definite estimation of large-sample covariance and spectral density matrices
Politis, D.N · 2005
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Resampling Methods for the Change Analysis of Dependent Data
C. Kirch · 2006
Earlier work this paper cites.
Sparse principal component analysis
H. Zou, T. Hastie, and R. Tibshirani · 2006
Cited alongside, same era.
A Simple Proof of the Restricted Isometry Property for Random Matrices
R. Baraniuk, M. Davenport, R. DeVore, and M. Wakin · 2008
Cited alongside, same era.
Regularized estimation of large covariance matrices
P. J. Bickel and E. Levina · 2008
Cited alongside, same era.
Detecting changes in the mean of functional observations
I. Berkes, R. Gabrys, L. Horváth, and P. Kokoszka · 2009
Cited alongside, same era.
Common Breaks in Means and Variances for Panel Data
J. Bai · 2010
Cited alongside, same era.
Compressed Fisher linear discriminant analysis: Classification of randomly projected data
R. J. Durrant and A. Kabán · 2010
Testing for parameter stability in nonlinear autoregressive models
C. Kirch and J. Tadjuidje Kamgaing · 2012
Later among the works it cites.
Structural breaks in time series
A. Aue and L. Horváth · 2013
Later among the works it cites.
Large covariance estimation by thresholding principal orthogonal complements
J. Fan, Y. Liao, and M. Mincheva · 2013
Later among the works it cites.
Multiscale change point inference
K. Frick, A. Munk, and H. Sieling · 2014
Closest in time.
Extensions of some classical methods in change point analysis
L. Horváth and G. Rice · 2014
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Adaptive Multivariate Global Testing
G. Minas, J. A. D. Aston, and N. Stallard · 2014
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Cited alongside, same era.
Weakly dependent functional data
S. Hörmann and P. Kokoszka · 2010
Cited alongside, same era.
Probability inequalities
Z. Lin and Z. Bai · 2010
Cited alongside, same era.
Analysis of changepoint models
I. Eckley, P. Fearnhead, and R. Killick · 2011
Cited alongside, same era.
A more powerful two-sample test in high dimensions using random projection
M. Lopes, L. Jacob, and M. J. Wainwright · 2011
Cited alongside, same era.
Mean shift testing in correlated data
M. Robbins, C. Gallagher, R. Lund, and A. Aue · 2011
Cited alongside, same era.
Darling–Erdős limit results for change–point detection in panel data
J. Chan, L. Horváth, and M. Hušková · 2012
Cited alongside, same era.
R. Srivastava, P. Li, and D. Ruppert · 2014
Closest in time.
Change-point detection in panel data via double cusum statistic
H. Cho · 2015
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Multiple-change-point detection for high dimensional time series via sparsified binary segmentation
H. Cho and P. Fryzlewicz · 2015
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Uniform change point tests in high dimension
M. Jirak · 2015
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Detection of changes in multivariate time series with applications to eeg data
C. Kirch, B. Mushal, and H. Ombao · 2015
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High-dimensional changepoint estimation via sparse projection
T. Wang and R. J. Samworth · 2016
Closest in time.