denseLinearShrinkEst {cvCovEst} | R Documentation |
Linear Shrinkage Estimator, Dense Target
Description
denseLinearShrinkEst()
computes the asymptotically
optimal convex combination of the sample covariance matrix and a dense
target matrix. This target matrix's diagonal elements are equal to the
average of the sample covariance matrix estimate's diagonal elements, and
its off-diagonal elements are equal to the average of the sample covariance
matrix estimate's off-diagonal elements. For information on this
estimator's derivation, see Ledoit and Wolf (2020) and
Schäfer and Strimmer (2005).
Usage
denseLinearShrinkEst(dat)
Arguments
dat |
A numeric |
Value
A matrix
corresponding to the estimate of the covariance
matrix.
References
Ledoit O, Wolf M (2020).
“The Power of (Non-)Linear Shrinking: A Review and Guide to Covariance Matrix Estimation.”
Journal of Financial Econometrics.
ISSN 1479-8409, doi:10.1093/jjfinec/nbaa007, nbaa007, https://academic.oup.com/jfec/advance-article-pdf/doi/10.1093/jjfinec/nbaa007/33416890/nbaa007.pdf.
Schäfer J, Strimmer K (2005).
“A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics.”
Statistical Applications in Genetics and Molecular Biology, 4(1).
doi:10.2202/1544-6115.1175, https://www.degruyter.com/view/journals/sagmb/4/1/article-sagmb.2005.4.1.1175.xml.xml.
Examples
denseLinearShrinkEst(dat = mtcars)