Maintainer: Timothy I. Cannings <timothy.cannings@ed.ac.uk>
Description: Implements the methodology of "Cannings, T. I. and Samworth, R. J. (2017) Random-projection ensemble classification, J. Roy. Statist. Soc., Ser. B. (with discussion), 79, 959--1035". The random projection ensemble classifier is a general method for classification of high-dimensional data, based on careful combination of the results of applying an arbitrary base classifier to random projections of the feature vectors into a lower-dimensional space. The random projections are divided into non-overlapping blocks, and within each block the projection yielding the smallest estimate of the test error is selected. The random projection ensemble classifier then aggregates the results of applying the base classifier on the selected projections, with a data-driven voting threshold to determine the final assignment.

Title: Graphical User Interface (GUI) for interactive R analysis sessions
Description: Poor Man's Gui: create interactive R analysis sessions
Packaged: Wed Oct 10 09:50:24 2007; lees

Packaged: Fri Jun 20 12:35:15 2008; lees

License: GNU General Public License (GPL)
Packaged: Thu Oct  4 16:05:04 2007; lees

Title: Graphical User Interface (GUI) for interactive R analysis

Title: Graphical User Interface (GUI) for Interactive R Analysis
Description: Really Poor Man's Graphical User Interface, used to create interactive R analysis sessions with simple R commands.

role = c("aut", "cre"),email = "jonathan.lees@unc.edu"), person("Jake", "Anderson", role = "ctb", email = "ajakef@gmail.com"))

Title: Recursively Partitioned Mixture Model
Maintainer: E. Andres Houseman <E_Andres_Houseman@brown.edu>
Description: Recursively Partitioned Mixture Model for Beta and
Gaussian Mixtures. This is a model-based clustering algorithm
that returns a hierarchy of classes, similar to hierarchical
clustering, but also similar to finite mixture models.
Packaged: Wed Sep 9 13:45:58 2009; ahousema

Packaged: Mon Nov 16 14:08:12 2009; ahousema

Gaussian Mixtures.  This is a model-based clustering algorithm