CaDENCE: Conditional Density Estimation Network Construction and Evaluation

Parameters of a user-specified probability distribution are modelled by a multi-layer perceptron artificial neural network. This framework can be used to implement probabilistic nonlinear models including mixture density networks, heteroscedastic regression models, zero-inflated models, and the like.

Version: 1.2.2
Depends: pso
Suggests: boot
Published: 2015-02-21
Author: Alex J. Cannon
Maintainer: Alex J. Cannon <acannon at eos.ubc.ca>
License: GPL-2
NeedsCompilation: no
Citation: CaDENCE citation info
CRAN checks: CaDENCE results

Downloads:

Reference manual: CaDENCE.pdf
Package source: CaDENCE_1.2.2.tar.gz
Windows binaries: r-devel: CaDENCE_1.2.2.zip, r-release: CaDENCE_1.2.2.zip, r-oldrel: CaDENCE_1.2.2.zip
OS X Snow Leopard binaries: r-oldrel: CaDENCE_1.2.2.tgz
OS X Mavericks binaries: r-release: CaDENCE_1.2.2.tgz
Old sources: CaDENCE archive