# hdrcde v3.3

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## 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.

# hdrcde: Highest Density Regions and Conditional Density Estimation

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")


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

## Functions in hdrcde

 Name Description plot.hdrconf Plot HDRs with confidence intervals hdrbw Highest Density Region Bandwidth hdrconf HDRs with confidence intervals maxtemp Daily maximum temperatures in Melbourne, Australia modalreg Nonparametric Multimodal Regression cde.bandwidths Bandwidth calculation for conditional density estimation hdr Highest Density Regions hdrscatterplot Scatterplot showing bivariate highest density regions lane2 Speed-Flow data for Californian Freeway BoxCox Box Cox Transformation cde Conditional Density Estimation hdr.2d Bivariate Highest Density Regions hdr.cde Calculate highest density regions continously over some conditioned variable. plot.cde Plots conditional densities No Results!