KL_dist: Kullback-Leibler for zero-mean Gaussian data
In alessandrocolombi/ACutils: Collection of utilities
View source: R/ACutils_export.R
KL_dist R Documentation
Kullback-Leibler for zero-mean Gaussian data
Description
Compute the Kullback-Leibler for zero-mean Gaussian distributed data. Can be used to measure the distance between the true underlying covariance (or precision) matrix and the estimated one.
Usage
KL_dist(Ktr, K)
Arguments
Ktr
the true matrix. Can be both covariance or precision
K
the estimated matrix. Can be both covariance or precision
Value
scalar, the distance between N(0, Ktr) and N(0, K)
alessandrocolombi/ACutils documentation built on March 3, 2023, 4:06 a.m.
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View source: R/ACutils_export.R
| KL_dist | R Documentation |
Kullback-Leibler for zero-mean Gaussian data
Description
Compute the Kullback-Leibler for zero-mean Gaussian distributed data. Can be used to measure the distance between the true underlying covariance (or precision) matrix and the estimated one.
Usage
KL_dist(Ktr, K)
Arguments
Ktr |
the true matrix. Can be both covariance or precision |
K |
the estimated matrix. Can be both covariance or precision |
Value
scalar, the distance between N(0, Ktr) and N(0, K)
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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