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: | 1.2.3 |
| Depends: | pso |
| Suggests: | boot |
| Published: | 2015-07-23 |
| 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 |
| Reference manual: | CaDENCE.pdf |
| Package source: | CaDENCE_1.2.3.tar.gz |
| Windows binaries: | r-devel: CaDENCE_1.2.3.zip, r-release: CaDENCE_1.2.3.zip, r-oldrel: CaDENCE_1.2.3.zip |
| OS X Snow Leopard binaries: | r-release: CaDENCE_1.2.3.tgz, r-oldrel: CaDENCE_1.2.2.tgz |
| OS X Mavericks binaries: | r-release: CaDENCE_1.2.3.tgz |
| Old sources: | CaDENCE archive |