Package: CaDENCE 1.2.5

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>.

Authors:Alex J. Cannon

CaDENCE_1.2.5.tar.gz
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CaDENCE.pdf |CaDENCE.html✨
CaDENCE/json (API)

# Install 'CaDENCE' in R:
install.packages('CaDENCE', repos = c('https://alexcannon.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • FraserSediment - Sediment and stream discharge data for Fraser River at Hope

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.45 score 28 scripts 263 downloads 32 exports 1 dependencies

Last updated 7 years agofrom:7c754e5e40. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-winOKNov 20 2024
R-4.5-linuxOKNov 20 2024
R-4.4-winOKNov 20 2024
R-4.4-macOKNov 20 2024
R-4.3-winOKNov 20 2024
R-4.3-macOKNov 20 2024

Exports:cadence.costcadence.evaluatecadence.fitcadence.initializecadence.predictcadence.reshapedbgammadblnormdbpareto2dbweibulldpareto2dummy.codegam.stylelogisticpbgammapblnormpbpareto2pbweibullppareto2qbgammaqblnormqbpareto2qbweibullqpareto2rbfrbgammarblnormrbpareto2rbweibullrpareto2rpropxval.buffer

Dependencies:pso