adacov: Adaptive Thresholding for Sparse Covariance Matrix Estimation
In qpsy/hotelhd: High dimensional Hotelling's T2 test
Description
Usage
Arguments
Value
References
Description
A templete function for adaptive thresholding for covariance matrix.
This method varies by how theta was defined, and what funtion form for
adaptive thresholding was used.
Usage
1
adacov(X, delta = 2, eta = 4)
Arguments
X
an n by p data matrix.
delta
a numeric value. A tuning parameter.
The default value of delta is 2, and is taken from Cai and Liu (2011).
Also, it can be chosen empirically through cross-validation.
eta
a numeric value. A shrinkage parameter. The greater value
shrink sparse values more.
Value
Test results
References
will be added
qpsy/hotelhd documentation built on May 26, 2019, 12:34 p.m.
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Description Usage Arguments Value References
Description
A templete function for adaptive thresholding for covariance matrix. This method varies by how theta was defined, and what funtion form for adaptive thresholding was used.
Usage
1 | adacov(X, delta = 2, eta = 4)
|
Arguments
X |
an n by p data matrix. |
delta |
a numeric value. A tuning parameter. The default value of delta is 2, and is taken from Cai and Liu (2011). Also, it can be chosen empirically through cross-validation. |
eta |
a numeric value. A shrinkage parameter. The greater value shrink sparse values more. |
Value
Test results
References
will be added
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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