Exercise Solution 3.17

  1. W has a singular covariance matrix because its components are linearly related.
  2. V has a non-singular covariance matrix. Although its components are related, that relationship in not linear.
  3. X has a non-singular covariance matrix because its components are not linearly related.
  4. Y has a singular covariance matrix because its components are linearly related.

 

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