ledoit_wolf: Ledoit and Wolf Shrinkage Estimator
In GGMncv: Gaussian Graphical Models with Nonconvex Regularization
Description
Usage
Arguments
Value
References
Examples
Description
Compute the Ledoit and Wolf shrinkage estimator of
the covariance matrix \insertCiteledoit2004wellGGMncv,
which can be used for the initial inverse covariance matrix
in ggmncv.
Usage
1
ledoit_wolf(Y, ...)
Arguments
Y
A data matrix (or data.frame) of dimensions n by p.
...
Currently ignored.
Value
Inverse correlation matrix.
References
\insertAllCited
Examples
1
2
3
4
5
6
7
8
# ptsd
Y <- ptsd[,1:5]
# shrinkage
ledoit_wolf(Y)
# non-reg
solve(cor(Y))
GGMncv documentation built on Dec. 15, 2021, 9:10 a.m.
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Description Usage Arguments Value References Examples
Description
Compute the Ledoit and Wolf shrinkage estimator of
the covariance matrix \insertCiteledoit2004wellGGMncv,
which can be used for the initial inverse covariance matrix
in ggmncv.
Usage
1 | ledoit_wolf(Y, ...)
|
Arguments
Y |
A data matrix (or data.frame) of dimensions n by p. |
... |
Currently ignored. |
Value
Inverse correlation matrix.
References
\insertAllCitedExamples
1 2 3 4 5 6 7 8 | # ptsd
Y <- ptsd[,1:5]
# shrinkage
ledoit_wolf(Y)
# non-reg
solve(cor(Y))
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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