Title: Visualization of multivariate, functions, sets, and data
(1) visualize multivariate density functions and density estimates
(2) visualize level sets with shape trees,
(3) visualize multivariate data with tail trees,
(4) visualize scales of multivariate density estimates with
(5) visualize anisotropic spread with 2D volume functions and
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.
Packaged: Thu Mar 30 10:47:49 2006; hornik

Packaged: Fri May 19 22:01:55 2006; hornik

Level set trees visualize mode structure,
shape trees visualize shapes of level sets of unimodal densities,
and tail trees visualize connected data sets.
but the package may be applied for visualizing other density estimates.

Package: denpro
Version: 0.9.0
Date: 2009-06-15
Title: Visualization of multivariate, functions, sets, and data
Author: Jussi Klemela <klemela@oulu.fi>
Maintainer: Jussi Klemela <klemela@oulu.fi>
Depends:
Description: 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. Level set
trees visualize mode structure, shape trees visualize shapes of
level sets of unimodal densities, and tail trees visualize
connected data sets. The kernel estimator is implemented but
the package may be applied for visualizing other density
estimates.
License: GPL (>= 2)
URL: http://www.rni.helsinki.fi/~jsk/denpro/
Packaged: Tue Jun 16 12:06:16 2009; jsk
Repository: CRAN
Date/Publication: 2009-06-16 13:28:21

Title: Visualization of Multivariate Functions, Sets, and Data
but the package may  also be applied for visualizing other density estimates.

Title: Density Estimation via Bayesian Inference Engines
Authors@R: person("Matt P.", "Wand", role = c("aut","cre"),
Description: Bayesian density estimates for univariate continuous random samples are provided using the Bayesian inference engine paradigm. The engine options are: Hamiltonian Monte Carlo, the no U-turn sampler, semiparametric mean field variational Bayes and slice sampling. The methodology is described in Wand and Yu (2020) <arXiv:2009.06182>.
Imports: MASS, nlme, Rcpp, methods, rstan
LinkingTo: BH, Rcpp, RcppArmadillo, RcppEigen, RcppParallel,
Author: Matt P. Wand [aut, cre] (<https://orcid.org/0000-0003-2555-896X>)