pca_outlier.r

library(MASS)

n_correlated = 99
correlation = 1

correlated_data <- mvrnorm(
  n_correlated, 
  mu = c(0,0), 
  Sigma = matrix(c(1, correlation, correlation, 1), ncol = 2), 
  empirical = TRUE
)

data_with_outlier = rbind(correlated_data, c(1, -1))

correlated_prc = prcomp(correlated_data, center=TRUE, scale=TRUE)
prc_with_outlier = prcomp(data_with_outlier, center=TRUE, scale=TRUE)

plot(data_with_outlier)
biplot(correlated_prc)
biplot(prc_with_outlier)