Robust Estimation of the Mean and Covariance Matrix for High Dimensional Time Series

Statistica Sinica ◽

10.5705/ss.202018.0185 ◽

2021 ◽

Author(s):

Danna Zhang

Keyword(s):

Time Series ◽

Covariance Matrix ◽

Robust Estimation ◽

High Dimensional ◽

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Robust Estimation of a High-Dimensional Integrated Covariance Matrix

SSRN Electronic Journal ◽

10.2139/ssrn.1996261 ◽

2012 ◽

Author(s):

Takayuki Morimoto ◽

Shuichi Nagata

Keyword(s):

Covariance Matrix ◽

Robust Estimation ◽

High Dimensional ◽

Integrated Covariance

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Robust estimation for the covariance matrix of multivariate time series based on normal mixtures

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2012.06.012 ◽

2013 ◽

Vol 57 (1) ◽

pp. 125-140 ◽

Author(s):

Byungsoo Kim ◽

Sangyeol Lee

Keyword(s):

Time Series ◽

Covariance Matrix ◽

Robust Estimation ◽

Multivariate Time Series ◽

Normal Mixtures

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Testing and estimating change-points in the covariance matrix of a high-dimensional time series

Journal of Multivariate Analysis ◽

10.1016/j.jmva.2019.104582 ◽

2020 ◽

Vol 177 ◽

pp. 104582

Author(s):

Ansgar Steland

Keyword(s):

Time Series ◽

Covariance Matrix ◽

Change Points ◽

High Dimensional

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Robust estimation of a high-dimensional integrated covariance matrix

Communications in Statistics - Simulation and Computation ◽

10.1080/03610918.2014.991038 ◽

2016 ◽

Vol 46 (2) ◽

pp. 1102-1112 ◽

Author(s):

Takayuki Morimoto ◽

Shuichi Nagata

Keyword(s):

Covariance Matrix ◽

Robust Estimation ◽

High Dimensional ◽

Integrated Covariance

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Simultaneous testing of the mean vector and covariance matrix among k populations for high-dimensional data

Communication in Statistics- Theory and Methods ◽

10.1080/03610926.2019.1639751 ◽

2019 ◽

pp. 1-22 ◽

Author(s):

Masashi Hyodo ◽

Takahiro Nishiyama

Keyword(s):

Covariance Matrix ◽

High Dimensional Data ◽

High Dimensional ◽

Simultaneous Testing ◽

The Mean ◽

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Statistical surveillance of the mean vector and the covariance matrix of nonlinear time series

AStA Advances in Statistical Analysis ◽

10.1007/s10182-013-0220-2 ◽

2013 ◽

Vol 98 (3) ◽

pp. 225-255 ◽

Author(s):

Robert Garthoff ◽

Iryna Okhrin ◽

Wolfgang Schmid

Keyword(s):

Time Series ◽

Covariance Matrix ◽

Nonlinear Time Series ◽

The Mean ◽

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Robust estimation of the mean vector for high-dimensional data set using robust clustering

Journal of Applied Statistics ◽

10.1080/02664763.2014.999030 ◽

2015 ◽

Vol 42 (6) ◽

pp. 1183-1205 ◽

Author(s):

Hamid Shahriari ◽

Orod Ahmadi

Keyword(s):

Robust Estimation ◽

High Dimensional Data ◽

High Dimensional ◽

Data Set ◽

Robust Clustering ◽

The Mean ◽

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A simultaneous testing of the mean vector and the covariance matrix among two populations for high-dimensional data

Test ◽

10.1007/s11749-017-0567-x ◽

2017 ◽

Vol 27 (3) ◽

pp. 680-699 ◽

Author(s):

Masashi Hyodo ◽

Takahiro Nishiyama

Keyword(s):

Covariance Matrix ◽

High Dimensional Data ◽

High Dimensional ◽

Simultaneous Testing ◽

The Mean ◽

Mean Vector ◽

Two Populations

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Robust Estimation of the Mean and Covariance Matrix from Data with Missing Values

Journal of the Royal Statistical Society Series C (Applied Statistics) ◽

10.2307/2347491 ◽

1988 ◽

Vol 37 (1) ◽

pp. 23 ◽

Author(s):

Roderick J. A. Little

Keyword(s):

Covariance Matrix ◽

Robust Estimation ◽

Missing Values ◽

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A Bayesian approach to estimation of a statistical change-point in the mean parameter for high dimensional non-linear time series

10.1117/12.2187474 ◽

2015 ◽

Author(s):

Darrin Speegle ◽

Robert Steward

Keyword(s):

Time Series ◽

Bayesian Approach ◽

Change Point ◽

Linear Time ◽

High Dimensional ◽

The Mean ◽

Statistical Change

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