shrink_mat: Shrunken covariance matrix
In Swarchal/charDirection: Principal Characteristic Direction
Description
Usage
Arguments
Value
Description
Calculates a shrunken covariance matrix to be passed as the demoninator
in the LDA formula. The shrunken matrix is in the subspace of the components
that capture 95% of the variation of the dataset.
Usage
1
shrink_mat(R, samples_count, r)
Arguments
R
PCA scores
samples_count
number of samples to explain 95% of the variance
r
regularisation factor to smooth covariance matrix in order to
reduce noise. 1 is no regularisatoin.
Value
covariance matrix
Swarchal/charDirection documentation built on May 9, 2019, 3:25 p.m.
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Description Usage Arguments Value
Description
Calculates a shrunken covariance matrix to be passed as the demoninator in the LDA formula. The shrunken matrix is in the subspace of the components that capture 95% of the variation of the dataset.
Usage
1 | shrink_mat(R, samples_count, r)
|
Arguments
R |
PCA scores |
samples_count |
number of samples to explain 95% of the variance |
r |
regularisation factor to smooth covariance matrix in order to reduce noise. 1 is no regularisatoin. |
Value
covariance matrix
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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