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 |
|---|---|
| Place of Publication | CRAN |
| Media of output | Online |
| Publication status | Accepted/In press - 17 Apr 2014 |
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Anestis Touloumis
- School of Arch, Tech and Eng - Principal Lecturer
- Computing and Mathematical Sciences Research Excellence Group
Person: Academic