KL_divergence: Compute KL-Divergence on two covariance matrices....
In cvsem: SEM Model Comparison with K-Fold Cross-Validation
View source: R/DistanceMetrics.R
KL_divergence R Documentation
Compute KL-Divergence on two covariance matrices. KL-Divergence corresponds to the
Maximum Wishart Likelihood (MWL) discrepancy described in \insertCiteCudeck1983cvsem.
Description
Compute KL-Divergence on two covariance matrices. KL-Divergence corresponds to the
Maximum Wishart Likelihood (MWL) discrepancy described in \insertCiteCudeck1983cvsem.
Usage
KL_divergence(implied_sigma, test_S)
Arguments
implied_sigma
Model implied covariances matrix from training set
test_S
Sample covariance matrix from test set
Value
KL-Divergence index
References
\insertAllCited()
cvsem documentation built on Aug. 13, 2022, 5:06 p.m.
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View source: R/DistanceMetrics.R
| KL_divergence | R Documentation |
Compute KL-Divergence on two covariance matrices. KL-Divergence corresponds to the Maximum Wishart Likelihood (MWL) discrepancy described in \insertCiteCudeck1983cvsem.
Description
Compute KL-Divergence on two covariance matrices. KL-Divergence corresponds to the Maximum Wishart Likelihood (MWL) discrepancy described in \insertCiteCudeck1983cvsem.
Usage
KL_divergence(implied_sigma, test_S)
Arguments
implied_sigma |
Model implied covariances matrix from training set |
test_S |
Sample covariance matrix from test set |
Value
KL-Divergence index
References
\insertAllCited()
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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