ShrinkCovMat: Shrinkage Covariance Matrix Estimators

Anestis Touloumis

ShrinkCovMat: Shrinkage Covariance Matrix Estimators

Research output: Non-textual output › Software

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

Access to Document

https://CRAN.R-project.org/package=ShrinkCovMatLicence: GNU GPL

Anestis Touloumis
- A.Touloumisbrighton.acuk
- 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

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 = apr,

day = "17",

language = "English",

}

TY - ADVS

T1 - ShrinkCovMat

T2 - Shrinkage Covariance Matrix Estimators

AU - Touloumis, Anestis

PY - 2014/4/17

Y1 - 2014/4/17

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

CY - CRAN

ER -

ShrinkCovMat: Shrinkage Covariance Matrix Estimators

Abstract

Access to Document

Fingerprint

Profiles

Anestis Touloumis

Cite this