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.


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The R package hdrcde provides tools for computing highest density regions in one and two dimensions, kernel estimates of univariate density functions conditional on one covariate, and multimodal regression.

Author: Rob J Hyndman with contributions from Jochen Einbeck and Matt Wand

This package implements the methods described in the following papers.

Installation

You can install the stable version on R CRAN.

install.packages('hdrcde', dependencies = TRUE)

You can install the development version from Github

# install.packages("devtools")
devtools::install_github("robjhyndman/hdrcde")

License

This package is free and open source software, licensed under GPL 3.

News

Version 3.3

  • More options for hdr.boxplot (thanks to Simon Carrignon)
  • More flexible hdr.den plots (thanks to Simon Carrignon)
  • Fixed colours in hdrscatterplot

Version 3.2

  • Updated hdr.den() to demonstrate the calculation of hdr more clearly (thanks to Dennis Freuer for the suggestion)
  • Added hdrscatterplot() function
  • Roxygenized the package
  • Added pkgdown site

Version 3.1

  • Added dependency on mvtnorm to avoid problems with ks.

Version 3.0

  • Reduced dependency on KernSmooth and changed ::: calls to ::
  • New functions hdr.2d() and plot.hdr2d() to return and plot bivariate HDR information.
  • Rewritten hdr.boxplot.2d() function.

Version 2.16

  • Replaced .Internal() calls with new .filled.contour() function.

Version 2.15

  • Added option to control limits of density estimate in hdr.boxplot.2d()

Version 2.14

  • Updated references for hdrbw().

Version 2.13

* Added color options to hdr.boxplot.2d().

Version 2.12

* Modified hdr(), hdr.boxplot() and hdr.den() to allow a Box-Cox transformation to be used when computing the density. This allows the density estimate to be non-zero only on the positive real line.

Version 2.11

  • Added hdrbw() from Matt Wand to compute better bandwidths for hdr(), hdr.den() and hdr.boxplot().
  • Fixed a few bugs in the help files.

Version 2.10

  • Bug fix in hdr.boxplot.2d(). The show.points option was not working.

Version 2.09

  • Bug fix: the a bandwidth in cde() when fw=TRUE and use.locfit=TRUE was twice as large as it should have been.

Version 2.08

* Bug fix in hdr.boxplot.2d(). It would sometimes plot outliers on a separate plot.
* New argument to hdr.boxplot.2d() to allow the density to be estimated using the kde() function from the ks package.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("hdrcde")

3.4 by Rob Hyndman, 10 months ago


https://pkg.robjhyndman.com/hdrcde/, https://github.com/robjhyndman/hdrcde


Report a bug at https://github.com/robjhyndman/hdrcde/issues


Browse source code at https://github.com/cran/hdrcde


Authors: Rob Hyndman [aut, cre, cph] , Jochen Einbeck [aut] , Matthew Wand [aut] , Simon Carrignon [ctb] , Fan Cheng [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports locfit, ash, ks, KernSmooth, ggplot2, RColorBrewer


Imported by RChronoModel, RFpredInterval, SIBER, curvHDR, rainbow, tRophicPosition, truelies.

Depended on by ArchaeoPhases, SimpleTable, meboot, siar.

Suggested by condvis, condvis2, piRF.


See at CRAN