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 languageEnglish
Place of PublicationCRAN
Media of outputOnline
Publication statusAccepted/In press - 17 Apr 2014

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Shrinkage estimator
Covariance matrix
Shrinkage
Estimator
Sample size

Cite this

@misc{83034e43c11d4aab9ff79080b70b32de,
title = "ShrinkCovMat: Shrinkage Covariance Matrix Estimators",
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.",
author = "Anestis Touloumis",
year = "2014",
month = "4",
day = "17",
language = "English",

}

ShrinkCovMat : Shrinkage Covariance Matrix Estimators. Touloumis, Anestis (Author/Creator). 2014. CRAN.

Research output: Non-textual outputSoftwareResearch

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N2 - 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.

AB - 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.

M3 - Software

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