ward_1d: Fit a fast version of the 1 dimensional Ward clustering...

In jchiquet/fusedanova: Univariate hierarchical clustering

Description

The Ward clustering algorithm is the more statistically grounded hierarchical clustering approach. This version is dedicated to clustering of univariate data (i.e., vector).

Usage

ward_1d(x, hclust = TRUE)

Arguments

x	a numeric vector of observation for n individuals.
hclust	boolean: should the result be outputed as an hclust object? Default is TRUE.

Value

an S3 object with class hclust or a data frame of the succesive fusions.

Examples

data(aves)
ward1d <- ward_1d(aves$weight)
plot(ward1d)

jchiquet/fusedanova documentation built on July 19, 2019, 12:49 a.m.