matjeffreys function

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

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

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.

Returns

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)