klfor2normals: klfor2normals Compute the Kullback-Leibler divergence for 2...
In RMBC: Robust Model Based Clustering
Description
Usage
Arguments
Value
Description
klfor2normals
Compute the Kullback-Leibler divergence for 2 normal multivariate distributions
Usage
1
klfor2normals(theta1.mu, theta1.sigma, theta2.mu, theta2.sigma)
Arguments
theta1.mu
the location parameter of the first distribution
theta1.sigma
the covariance matrix of the first distribution
theta2.mu
the location parameter of the second distribution
theta2.sigma
the covariance matrix of the second distribution
Value
the K-L divergence.
RMBC documentation built on July 22, 2021, 9:07 a.m.
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Description Usage Arguments Value
Description
klfor2normals Compute the Kullback-Leibler divergence for 2 normal multivariate distributions
Usage
1 | klfor2normals(theta1.mu, theta1.sigma, theta2.mu, theta2.sigma)
|
Arguments
theta1.mu |
the location parameter of the first distribution |
theta1.sigma |
the covariance matrix of the first distribution |
theta2.mu |
the location parameter of the second distribution |
theta2.sigma |
the covariance matrix of the second distribution |
Value
the K-L divergence.
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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