pcplot: Principal Component Plots

In seijikoike/pcplot: Create PC plots and Scree plots

Description

Takes a data set and plots principal components against each other with ggplot.

Usage

pcplot(data, xpc, ypc, cor = TRUE, control = FALSE, group = NA,
  labelled = FALSE, biplot = FALSE)

Arguments

data	A set of predictor values
xpc	Principal component to plot along the x-axis
ypc	Principal compenent to plot along y-axis
cor	Indicates to use correlation for PCA. Defaults to TRUE
control	Indicates if user wants to customize ggplot rather than the default setting. Defaults to FALSE.
group	A vector indicating which group the observation belongs to. Defaults to NA.
labelled	Indicates whether or not to label the observations. Defaults to FALSE.
biplot	Allows user to plot vectors of loadings of each variable

Examples

library(ggplot2)
data("USArrests")
pcplot(USArrests, 1, 2, labelled = TRUE)

data("longley")
longley$Group <- ifelse(longley$Year <= 1954, "a", "b")
pcplot(longley[,-c(6:8)], 1, 2, group = longley$Group, labelled = TRUE)

seijikoike/pcplot documentation built on May 22, 2019, 10:55 p.m.