Problem 2049. Six Steps to PCA - Step 2: Covariance

Previous problems in this series

• Step 1: Centre and Standardize

Step 2: Covariance

For the second step we want the covariance matrix of the centred and standardized data that we calculated in Step 1. We could conveniently use Matlab's cov function, but this repeats much of what we've already done, for instance centering by removing the mean. It also has to deal with a wider range of possible inputs, whereas we have a very well specified starting point.

Task

Build on the code produced for Step 1 by writing a function to calculate the covariance matrix of the centred and standardized data matrix.

Add the following field to those already produced by your zscore function.

• Cov: a square matrix of covariances

Tips

• It's not as complicated as it sounds. Write one new line of code.
• Don't just call Matlab's own cov function.
• Keep to the structure of the code template with zscore as a local function.