kld: Kullback-Leibler Divergence

Description Usage Arguments Value Author(s) References Examples

Description

Estimates the Kullback-Leibler Divergence which measures how one probability distribution diverges from the original distribution (equivalent means are assumed) Matrices must be positive definite inverse covariance matrix for accurate measurement. This is a relative metric

Usage

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kld(base, test)

Arguments

base

Full or base model

test

Reduced or testing model

Value

A value greater than 0. Smaller values suggest the probability distribution of the reduced model is near the full model

Author(s)

Alexander Christensen <alexpaulchristensen@gmail.com>

References

Kullback, S., & Leibler, R. A. (1951). On information and sufficiency. The Annals of Mathematical Statistics, 22, 79-86.

Examples

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A1 <- solve(cov(neoOpen))

## Not run: 
A2 <- (neoOpen)

kld_value <- kld(A1, A2)

## End(Not run)

NetworkToolbox documentation built on May 28, 2021, 5:11 p.m.