plot.clusters.rows: plot.clusters.rows

In gianmarcoalberti/CAseriation: Contingency table seriation by means of Correspondence Analysis.

Description

This function returns the Correspondence Analysis scatterplot of row categories, with points' colour according to the clusters to which points belong. A tab delimited .txt file is also created (in the R working directory) containing the cluster membership for each row category.

Usage

## S3 method for class 'clusters.rows'
plot(data, x = 1, y = 2, bp = FALSE, varwidth = FALSE)

Arguments

x, y:	The dimensions to be plotted (1st and 2nd by default).
data:	Dataframe containing the contingency table to be analysed.
bp:	logical value (TRUE/FALSE). TRUE displays boxplots of row coordinates by cluster, in order to visually gauge the degree of separation between clusters. FALSE is default.
varwidth:	logical value (TRUE/FALSE). TRUE sets the width of the boxplots proportional to the groups size. This helps in eyeballing the size of the clusters being compared. FALSE is default.

Examples

data("perfect_seriation"): load the dataset 'perfect_seriation'
plot.clusters.rows (perfect_seriation,1,3): plot the Correspondence Analysis scatterplot of row categories (using the 'perfect_seriation' dataframe), displaying the 1 and 3 dimensions.
plot.clusters.rows (cemetery,1,2,bp=TRUE,varwidth=TRUE): plot the Correspondence Analysis scatterplot of row categories (using the 'cemetery' dataframe), displaying the 1 and 2 dimension. Boxplots of row coordinates (on the selected dimensions) by cluster are also displayed, with size proportional to the size of the clusters.

gianmarcoalberti/CAseriation documentation built on May 17, 2019, 4:19 a.m.