FastICA Algorithms to perform ICA and Projection Pursuit

J L Marchini <marchini@stats.ox.ac.uk>, C Heaton
        <chrisheaton99@yahoo.com> and B D Ripley
        <ripley@stats.ox.ac.uk>

Implementation of FastICA algorithm to perform Independent
        Component Analysis (ICA) and Projection Pursuit.

Estimation of (Local) False Discovery Rates and Higher Criticism

This package allows to estimate both tail area-based false 
   discovery rates (Fdr) as well as local false discovery rates (fdr) for a 
   variety of null models (p-values, z-scores, correlation coefficients,
   t-scores).  The proportion of null values and the parameters of the null 
   distribution are adaptively estimated from the data.  In addition, the package 
   contains functions for non-parametric density estimation (Grenander estimator), 
   for monotone regression (isotonic regression and antitonic regression with weights),
   for computing the greatest convex minorant (GCM) and the least concave majorant (LCM), 
   for the half-normal and correlation distributions, and for computing
   empirical higher criticism (HC) scores and the corresponding decision threshold.

A rewrite of the graphics layout capabilities, plus some
  support for interaction

Infrastructure for manipulating intervals on sequences

The package provides efficient low-level and highly reusable S4
	classes for storing ranges of integers, RLE vectors (Run-Length
	Encoding), and, more generally, data that can be organized
	sequentially (formally defined as Vector objects), as well as views
	on these Vector objects.
	Efficient list-like classes are also provided for storing big
	collections of instances of the basic classes. All classes in
	the package use consistent naming and share the same rich and
	consistent "Vector API" as much as possible.

R (>= 2.8.0), methods, utils, stats, BiocGenerics (>= 0.7.7)

methods, utils, stats, BiocGenerics, stats4

The following files in the 'src' directory are licensed
for all use by Jim Kent, in a manner compatible with the
Artistic 2.0 license: common.c/h, memalloc.c/h, localmem.c/h,
hash.c/h, errabort.c/h, rbTree.c/h, dlist.c/h, errCatch.h