ADPclust: Fast Clustering Using Adaptive Density Peak Detection

An implementation of ADPclust clustering procedures (Fast Clustering Using Adaptive Density Peak Detection). The work is built and improved upon the idea of Rodriguez and Laio (2014)<doi:10.1126/science.1242072>. ADPclust clusters data by finding density peaks in a density-distance plot generated from local multivariate Gaussian density estimation. It includes an automatic centroids selection and parameter optimization algorithm, which finds the number of clusters and cluster centroids by comparing average silhouettes on a grid of testing clustering results; It also includes a user interactive algorithm that allows the user to manually selects cluster centroids from a two dimensional "density-distance plot". Here is the research article associated with this package: "Wang, Xiao-Feng, and Yifan Xu (2015)<doi:10.1177/0962280215609948> Fast clustering using adaptive density peak detection." Statistical methods in medical research". url:

Version: 0.7
Depends: R (≥ 3.0.0)
Imports: dplyr, cluster, fields, knitr
Suggests: rmarkdown, testthat
Published: 2016-10-15
Author: Yifan (Ethan) Xu [aut, cre], Xiao-Feng Wang [aut]
Maintainer: Yifan (Ethan) Xu <ethan.yifanxu at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: ADPclust citation info
Materials: README
In views: Cluster
CRAN checks: ADPclust results


Reference manual: ADPclust.pdf
Vignettes: ADPclust-vignette
Package source: ADPclust_0.7.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: ADPclust_0.7.tgz
OS X Mavericks binaries: r-oldrel: ADPclust_0.7.tgz
Old sources: ADPclust archive


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