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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.

This package implements the methods described in the following papers.

- Rob J Hyndman (1996) "Computing and graphing highest density regions".
*American Statistician*,**50**, 120-126. - Rob J Hyndman and David Bashtannyk (1996) "Estimating and visualizing conditional densities".
*Journal of Computational and Graphical Statistics*,**5**, 315-336. - David Bashtannyk, Rob J Hyndman (2001) "Bandwidth selection for kernel conditional density estimation".
*Computational Statistics and Data Analysis***36**(3), 279-298. - Rob J Hyndman and Qiwei Yao (2002) "Nonparametric estimation and symmetry tests for conditional density functions".
*Journal of Nonparametric Statistics*,**14**(3), 259-278. - Einbeck, J., and Tutz, G. (2006). "Modelling beyond regression functions: an application of multimodal regression to speed-flow data".
*Journal of the Royal Statistical Society, Series C*,**55**, 461-475. - Richard J Samworth and Matthew P Wand (2010) "Asymptotics and optimal bandwidth selection for highest density region estimation".
*The Annals of Statistics*,**38**, 1767-1792.

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.

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