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")

3.3 by Rob Hyndman, 6 months ago


http://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 [ctb] , Matthew Wand [ctb]


Documentation:   PDF Manual  


GPL-3 license


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


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

Depended on by ArchaeoPhases, SimpleTable, siar.

Suggested by condvis.


See at CRAN