sctr: Clustering 2D-scatterplot

In EMbC: Expectation-Maximization Binary Clustering

Clustering 2D-scatterplot

Description

sctr generates a scatterplot from a binClst_instance, showing clusters in different colors.

Usage

sctr(obj, ...)

## S4 method for signature 'binClst'
sctr(obj, ref = NULL, showVars = NULL, showClst = NULL, bg = NULL, ...)

## S4 method for signature 'binClstStck'
sctr(obj, ref = NULL, showVars = NULL, showClst = NULL, ...)

Arguments

obj	A binClst_instance.
...	Parameters ref, showVars and showClst are optional.
ref	A numeric vector with expert/reference labeling for visual validation of the clustering. A second binClst_instance to be compared with the former.
showVars	When the number of variables is greater than two, a length 3 numeric vector indicating one splitting variable and two variables to be scattered (given in that order).
showClst	When the number of variables is greater than two, a numeric vector (of variable length) indicating a subset of the clusters that will be shown in the scatter plot. This is useful in case of overlapping clusters.
bg	A valid colour to be used as background colour for multivariate scatterplots. By default a light-grey colour is used to enhance data points visibility.

Examples

# -- apply EMbC to the example path --
mybcp <- stbc(expth,info=-1)
# -- show the scatterplot compared with expert labeling--
sctr(mybcp,expth$lbl)

EMbC documentation built on Oct. 3, 2023, 5:07 p.m.