FindH

dimension of data. The number of variables.

methods to calculate h. The valid options are (case insensitive) "amise" or "rot".

htype


Find bandwidth h from the number of observations n and the dimension p.


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:
http://smm.sagepub.com/content/early/2015/10/15/0962280215609948.abstract.

FindH: Find bandwidth h.

Description

Usage

Arguments

Value