matjeffreys: Matrix of the Jeffreys measures (symmetrised Kullback-Leibler...

In dad: Three-Way / Multigroup Data Analysis Through Densities

Matrix of the Jeffreys measures (symmetrised Kullback-Leibler divergences) between Gaussian densities

Description

Computes the matrix of Jeffreys measures between several multivariate (p > 1) or univariate (p = 1) Gaussian densities, given samples.

Usage

matjeffreys(x)

Arguments

x	object of class "folder" containing the data. Its elements have only numeric variables (observations of the probability densities). If there are non numeric variables, there is an error.

Value

Positive symmetric matrix whose order is equal to the number of densities, consisting of pairwise Jeffreys measures between the Gaussian densities.

Author(s)

Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Gilles Hunault, Sabine Demotes-Mainard

See Also

matjeffreyspar if the parameters of the Gaussian densities are known.

Examples

    data(roses)
    
    # Multivariate:
    X <- as.folder(roses[,c("Sha","Den","Sym","rose")], groups = "rose")
    summary(X)
    matjeffreys(X)
    
    # Univariate :
    X1 <- as.folder(roses[,c("Sha","rose")], groups = "rose")
    summary(X1)
    matjeffreys(X1)

dad documentation built on Aug. 30, 2023, 5:06 p.m.