I want to understand how to use the covariance matrix to get principal components?
If I have a usual data matrix n x p in which Y is the matrix and S is the sample variance-covariance matrix how can I use this covariance matrix (S) to get all principal components? And from that can I get the variance-covariance matrix of the principal components? If so what type of matrix would be and what does it mean? I need an intuitive approach using mathematics to help me to understand this.
