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>.

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Description file content

Package
CaDENCE
Type
Package
Title
Conditional Density Estimation Network Construction and Evaluation
Version
1.2.5
Author
Alex J. Cannon
Maintainer
Alex J. Cannon
Description
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) .
License
GPL-2
Suggests
boot
Depends
pso
LazyLoad
yes
NeedsCompilation
no
Repository
CRAN
Packaged
2017-12-04 22:54:00 UTC; ECPACIFIC+cannona
Date/Publication
2017-12-05 04:05:17 UTC

install.packages('CaDENCE')

1.2.5

6 days ago

Alex J. Cannon

GPL-2

Depends on

pso

Suggests

boot

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