ggscree: This function produces a simple scree plot

In mulgar: Functions for Pre-Processing Data for Multivariate Data Visualisation using Tours

This function produces a simple scree plot

Description

Takes a PCA object returned by prcomp(), extracts the standard deviations of the principal components (PC), and plots these against the PC number. The guidance line assumes that all of the variables have been standardised prior to PCA.

Usage

ggscree(pc, q = 2, guide = TRUE, cumulative = FALSE)

Arguments

pc	PCA object
q	number of principal components to show, default 2 (you should change)
guide	logical whether to compute and add a typical value of the variance, if the data was full-dimensional
cumulative	logical whether to draw cumulative variance

Value

scree a ggplot object

Examples

data(aflw)
aflw_std <- apply(aflw[,7:35], 2, function(x)
                    (x-mean(x, na.rm=TRUE))/
							       sd(x, na.rm=TRUE))
aflw_pca <- prcomp(aflw_std[,c("goals","behinds",
                               "kicks","disposals")])
ggscree(aflw_pca, q=3)

mulgar documentation built on April 12, 2025, 1:23 a.m.