Open Access
2016 Discussion of “Estimating structured high-dimensional covariance and precision matrices: Optimal rates and adaptive estimation”
Debashis Paul, Lili Wang
Electron. J. Statist. 10(1): 74-80 (2016). DOI: 10.1214/15-EJS1019

Abstract

In this discussion, we present a brief overview of recent works on the behavior of summary statistics for high-dimensional observations that are time-dependent, and the inference on parameters associated with high-dimensional time series, with emphasis on covariance and auto-covariance matrices.

Citation

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Debashis Paul. Lili Wang. "Discussion of “Estimating structured high-dimensional covariance and precision matrices: Optimal rates and adaptive estimation”." Electron. J. Statist. 10 (1) 74 - 80, 2016. https://doi.org/10.1214/15-EJS1019

Information

Received: 1 March 2015; Published: 2016
First available in Project Euclid: 17 February 2016

zbMATH: 1331.62276
MathSciNet: MR3466176
Digital Object Identifier: 10.1214/15-EJS1019

Subjects:
Primary: 62H99

Keywords: Covariance matrix , Principal Component Analysis , spiked covariance model , Stieltjes transform

Rights: Copyright © 2016 The Institute of Mathematical Statistics and the Bernoulli Society

Vol.10 • No. 1 • 2016
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