matddjeffreyspar

Computes the matrix of Jeffreys divergences between several multivariate or univariate discrete probability distributions on the same support (which can be a Cartesian product of \(q\) sets), given the probabilities of the states (which are \(q\)-tuples) of the support.

The data consist of a set of variables measured on several groups of individuals. To each group is associated an estimated probability density function. The package provides tools to create or manage such data and functional methods (principal component analysis, multidimensional scaling, cluster analysis, discriminant analysis...) for such probability densities.

Pierre Santagostini

Three-Way / Multigroup Data Analysis Through Densities

Rachid Boumaza

Smail Yousfi

Gilles Hunault

Julie Bourbeillon

Besnik Pumo

Sabine Demotes-Mainard

matddjeffreyspar function

<dl> <dt>freq</dt>
<dd>list of arrays. Their <code>dim</code> attribute is a vector with length \(q\), its elements containing the numbers of levels of the \(sets\). Each array contains the probabilities of the discrete distribution on the same support.</dd></dl>

Arguments

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

Author

Matrix of divergences between discrete probability densities given the probabilities on their common support — matddjeffreyspar

<dl>

 <dt>freq</dt>
<dd>list of arrays. Their <code>dim</code> attribute is a vector with length \(q\), its elements containing the numbers of levels of the \(sets\). Each array contains the probabilities of the discrete distribution on the same support.</dd>

</dl>

matddjeffreyspar: Matrix of divergences between discrete probability densities given the probabilities on their common support

Description

Usage

Value

Arguments

Author

References

See Also