rags2ridges: KLdiv.fused – R documentation

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KLdiv.fused

Fused Kullback-Leibler divergence for sets of distributions

Description

Function calculating the Kullback-Leibler divergence between two sets of multivariate normal distributions. In other words, it calculates a weigthed mean of Kullback-Leibler divergences between multiple paired normal distributions.

Usage

KLdiv.fused(MtestList, MrefList, StestList, SrefList, ns, symmetric = FALSE)

Arguments

`MtestList`	A `list` of mean vectors of the approximating multivariate normal distribution for each class. Assumed to be zero vectors if not supplied.
`MrefList`	A `list` of mean vectors of the reference multivariate normal distribution for each class. Assumed to be zero vectors if not supplied.
`StestList`	A `list` of covariance matrices of the approximating multivariate normal distribtuion for each class. Usually a `list` of sample covariance matrices.
`SrefList`	A `list` of covariance matrices of the references multivariate normal distribtuion for each class. Usually a `list` of the population or reference covariance matrices.
`ns`	a `numeric` of the same length as the previous arguments giving the sample sizes. Used as weights in the weighted mean.
`symmetric`	a `logical` indicating if original symmetric version of KL divergence should be calculated.

Value

Function returns a numeric representing the (optionally symmetric) fused Kullback-Leibler divergence.

Author(s)

Anders Ellern Bilgrau, Wessel N. van Wieringen, Carel F.W. Peeters <cf.peeters@vumc.nl>

Examples

# Create some toy data
n <- c(40, 60, 80)
p <- 10
Stest <- replicate(length(n), diag(p), simplify = FALSE)
Sref <- createS(n, p = p)

KLdiv.fused(StestList = Stest, SrefList = Sref, ns = n, symmetric = FALSE)
KLdiv.fused(StestList = Stest, SrefList = Sref, ns = n, symmetric = TRUE)

rags2ridges

Ridge Estimation of Precision Matrices from High-Dimensional Data

v2.2.4

GPL (>= 2)

Authors

Carel F.W. Peeters [cre, aut], Anders Ellern Bilgrau [aut], Wessel N. van Wieringen [aut]

Initial release