Choosing the number of PCs
One of the main challenges with PCA is selecting the number of PCs, which can be done by determining the amount of the cumulative proportion of variance that is explained. We will use this method to select the number of PCs needed to explain 95% of the variation in the state.x77 data. The proportion of variation explained by each PC is preloaded for you as the object pca.pvar.
This exercise is part of the course
Multivariate Probability Distributions in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Proportion of variance explained by each principal component
# Cumulative variance explained plot
plot(___, xlab = "Principal component", ylab = "Cumulative Proportion of variance explained", ylim = c(0,1), type = 'b')
grid()