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, etc. following Cannon (2012) doi:10.1016/j.cageo.2011.08.023.
- Version1.2.5
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release12/05/2017
Documentation
Team
Alex J. Cannon
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Depends1 package
- Suggests1 package