Packaged: 2015-07-15 13:09:33 UTC; bryanhanson

Package: FuncMap
Type: Package
Title: Hive Plots of R Package Function Calls
Version: 1.0
Date: 2010-12-20
Author: Bryan A. Hanson DePauw University, Greencastle Indiana USA
Maintainer: Bryan A. Hanson <hanson@depauw.edu>
Description: FuncMap analyzes the function calls in an R package and
creates a hive plot of the calls, dividing them among functions
that only make outgoing calls (sources), functions that have
only incoming calls (sinks), and those that have both incoming
calls and make outgoing calls (managers).  Function calls can
be mapped by their absolute numbers, their normalized absolute
numbers, or their rank.  FuncMap should be useful for comparing
packages at a high level for their overall design.  Plus, it's
just plain fun.  The hive plot concept was developed by Martin
Krzywinski (mkweb.bcgsc.ca/linnet/) and inspired this package.
License: GPL-3
LazyLoad: yes
Depends: grid, mvbutils
Suggests: lattice
Packaged: 2010-12-21 00:42:42 UTC; bryanhanson
Repository: CRAN
Date/Publication: 2010-12-21 16:54:38

person("Richard", "Groenewald", role = "ctb"),
person("Barinder", "Thind", email = "barinder.thi@gmail.com", role = c("aut", "cre", "cph")),
Description: A collection of functions which fit functional neural network models. In
other words, this package will allow users to build deep learning models
that have either functional or scalar responses paired with functional and
scalar covariates. We implement the theoretical discussion found
in Thind, Multani and Cao (2020) <arXiv:2006.09590> through the help of a main fitting and
prediction function as well as a number of helper functions to assist with
cross-validation, tuning, and the display of estimated functional weights.
Imports: keras, tensorflow, fda.usc, fda, ggplot2, ggpubr, caret,
pbapply, reshape2, flux, doParallel, foreach, Matrix

Title: A package for functional data clustering.
Author: Mohamed Soueidatt <mohamed.soueidatt@inria.fr>, <msoueidatt@gmail.com>*.
Description: This packages proposes a model-based clustering algorithm for
multivariate functional data. The parametric mixture model, based on the
assumption of normality of the principal components resulting from a
multivariate functional PCA, is estimated by an EM-like algorithm. The main
advantage of the proposed algorithm is its ability to take into account the
Collate: 'cpp_data.R' 'funclust.r' 'input.R' 'output.R' 'plot.R'