In R, there are several functions from different packages that allow us to perform PCA.
For this reason, PCA allows to reduce a “complex” data set to a lower dimension in order to reveal the structures or the dominant types of variations in both the observations and the variables. Principal Component Analysis ( PCA) is a multivariate technique that allows us to summarize the systematic patterns of variations in the data.įrom a data analysis standpoint, PCA is used for studying one table of observations and variables with the main idea of transforming the observed variables into a set of new variables, the principal components, which are uncorrelated and explain the variation in the data. 5 functions to do Principal Components Analysis in R Posted on June 17, 2012
