# Fast Clustering Using Adaptive Density Peak Detection

## Documentation for package ‘ADPclust’ version 0.7

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

adpclust | Fast Clustering Using Adaptive Density Peak Detection
AMISE | AMISE bandwidth
clust10 | 1000 5-dimensional data points that form ten clusters
clust3 | 90 2-dimensional data points that form three clusters
clust5 | 500 5-dimensional data points that form five clusters
clust5.1 | 500 5-dimensional data points that form five clusters
dat_gene | 243-dimensional gene expression data of 38 patients (243 genes)
defCol | Default colors
FindCentersAutoD | Automatically finds centers with diagonal f(x) vs delta(x) thresholds
FindCentersAutoV | Automatically find centers with vertical threshold
FindClustersAuto | Automatically find cluster assignment given f and delta.
FindClustersGivenCenters | Find cluster assignments given centers and distance matrix
FindClustersManual | User-interactive routine to find clusters
FindDistm | Find the distance matrix from data.
FindFD | Find f and delta from distance matrix.
FindH | Find bandwidth h.
plot.adpclust | Visualize the result of adpclust()
ROT | Calculate ROT bandwidth
summary.adpclust | Summary of adpclust