Visualization of multivariate density functions and estimates with level set trees and shape trees, and visualization of multivariate data with tail trees
The package provides functions to construct level set trees
of some multivariate density estimates and density functions.
With level set trees we may visualize
the number and location of modes,
the relative importance of the modes,
the barycenters of the separated regions of level sets,
and skewness and kurtosis of the density.
The visualization methods may be applied in exploratory data analysis,
to make graphical inference on the existence of the modes,
and to apply graphical methods to choose the smoothing parameter.
The package provides also functions to construct shape trees of connected level sets.
Visualization with level set trees and shape trees is in many cases more
effective and easy to use than the method of looking at slices and
projections of a density function.
The package implements the kernel estimator
but the package may be applied for visualizing
other density estimates, which have to be setwise constant.
The package provides also tools to visualize multivariate data;
it provides parallel tail tree plots and cumulative tail frequency plots.

Visualization of multivariate, functions, sets, and data
The package provides tools to
(1) visualize multivariate density functions and density estimates
with level set trees,
(2) visualize level sets with shape trees,
(3) visualize multivariate data with tail trees,
(4) visualize scales of multivariate density estimates with
mode graphs and branching maps, and
(5) visualize anisotropic spread with 2D volume functions and
2D probability conetent functions.
With level set trees one visualizes mode structure,
with shape trees one visualizes shapes of level sets of unimodal densities,
and with tail trees one visualizes connected data sets.
The kernel estimator is implemented
but the package may be applied for visualizing
other density estimates, which have to be setwise constant.