hdrcde: Highest Density Regions and Conditional Density Estimation

Computation of highest density regions in one and two dimensions, kernel estimation of univariate density functions conditional on one covariate,and multimodal regression.

Version: 3.4
Depends: R (≥ 2.15)
Imports: locfit, ash, ks, KernSmooth, ggplot2, RColorBrewer
Published: 2021-01-18
Author: Rob Hyndman ORCID iD [aut, cre, cph], Jochen Einbeck ORCID iD [aut], Matthew Wand ORCID iD [aut], Simon Carrignon ORCID iD [ctb], Fan Cheng ORCID iD [ctb]
Maintainer: Rob Hyndman <Rob.Hyndman at monash.edu>
BugReports: https://github.com/robjhyndman/hdrcde/issues
License: GPL-3
URL: https://pkg.robjhyndman.com/hdrcde/, https://github.com/robjhyndman/hdrcde
NeedsCompilation: yes
Citation: hdrcde citation info
Materials: README NEWS
CRAN checks: hdrcde results

Documentation:

Reference manual: hdrcde.pdf

Downloads:

Package source: hdrcde_3.4.tar.gz
Windows binaries: r-devel: hdrcde_3.4.zip, r-release: hdrcde_3.4.zip, r-oldrel: hdrcde_3.4.zip
macOS binaries: r-release (arm64): hdrcde_3.4.tgz, r-oldrel (arm64): hdrcde_3.4.tgz, r-release (x86_64): hdrcde_3.4.tgz
Old sources: hdrcde archive

Reverse dependencies:

Reverse depends: meboot
Reverse imports: curvHDR, rainbow, RChronoModel, RFpredInterval, SIBER, truelies
Reverse suggests: condvis, condvis2, piRF, smidm

Linking:

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