Simulate real and complex numbers from distributions of their
magnitude and arguments. Optionally, the magnitudes and/or arguments may
be fixed in almost arbitrary ways. Plot density and distribution
functions with automatic selection of suitable regions.  Small programming
utilities: check if an object is identical to NA, count positional
arguments in a call, set intersection of more than two sets, check if an
argument is unnamed, compute the graph of S4 classes in packages.
parse_text.R sim_numbers.R isNA.R mintersect.R pad.R args.R
history.R cdf2qf.R S4utils.R

parse_text.R sim_numbers.R isNA.R mintersect.R pad.R args.R
history.R cdf2qf.R S4utils.R pseudoInverse.R

Utilities for Simulation, Plots, Quantile Functions and
Programming
testthat (>= 3.0.0), classGraph, graph, Rgraphviz
Plot density and distribution functions with automatic selection of
suitable regions. Numerically invert (compute quantiles) distribution
functions. Simulate real and complex numbers from distributions of their
magnitude and arguments. Optionally, the magnitudes and/or arguments may
be fixed in almost arbitrary ways. Create polynomials from roots given in
Cartesian or polar form. Small programming utilities: check if an object
is identical to NA, count positional arguments in a call, set
intersection of more than two sets, check if an argument is unnamed,
compute the graph of S4 classes in packages.
parse_text.R sim_numbers.R isNA.R mintersect.R pad.R args.R
history.R cdf2qf.R S4utils.R pseudoInverse.R rpoly.R

Theresa Scharl, Ingo Voglhuber, Friedrich Leisch
Visualize cluster results and investigate additional
properties of clusters using interactive neighbourhood graphs. By
clicking on the node representing the cluster, information about
the cluster is provided using additional graphics or summary
statistics. For microarray data, tables with links to genetic
databases like gene ontolgy can be created for each cluster.
graphics, methods, flexclust (>= 1.0-0), Rgraphviz

Visualize cluster results and investigate additional
properties of clusters using interactive neighbourhood graphs.
By clicking on the node representing the cluster, information
about the cluster is provided using additional graphics or
summary statistics. For microarray data, tables with links to
genetic databases like gene ontolgy can be created for each
cluster.