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>.

Package details

AuthorAlex J. Cannon
MaintainerAlex J. Cannon <[email protected]>
LicenseGPL-2
Version1.2.5
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("CaDENCE")

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CaDENCE documentation built on Dec. 5, 2017, 9:03 a.m.