Abstract
Provides nonparametric Steinian shrinkage estimators of the covariance matrix that are suitable in high dimensional settings, that is when the number of variables is larger than the sample size.
Original language | English |
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Place of Publication | CRAN |
Media of output | Online |
Publication status | Accepted/In press - 17 Apr 2014 |
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Dive into the research topics of 'ShrinkCovMat: Shrinkage Covariance Matrix Estimators'. Together they form a unique fingerprint.Profiles
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Anestis Touloumis
- School of Arch, Tech and Eng - Principal Lecturer
- Centre for Secure, Intelligent and Usable Systems - Associate Director of Researcher Development
- Mathematical Sciences Research and Enterprise Group
Person: Academic