Take the 2-minute tour ×
Mathematics Stack Exchange is a question and answer site for people studying math at any level and professionals in related fields. It's 100% free, no registration required.

How to find a covariance matrix from given mean values. e.g. Given mean values m1= (1/4) (3 1 1)T and m2 = (1/4) (1 3 3)T

share|improve this question

put on hold as off-topic by 900 sit-ups a day, Kirill, glace, Adam Hughes, T. Bongers yesterday

This question appears to be off-topic. The users who voted to close gave this specific reason:

  • "This question is missing context or other details: Please improve the question by providing additional context, which ideally includes your thoughts on the problem and any attempts you have made to solve it. This information helps others identify where you have difficulties and helps them write answers appropriate to your experience level." – Kirill, glace, Adam Hughes
If this question can be reworded to fit the rules in the help center, please edit the question.

What do you mean by "mean values"? You can not determine the covariance matrix given only the means of two random vectors. (The covariance matrix could be any nonnegative definite matrix.) –  passerby51 May 13 '12 at 4:34

1 Answer 1

You need the original observations to get covariance terms because a variance sums (Xi - Xs sample mean)^2 terms and covariances sum terms like (Xi-Xs sample mean) (Yi-Ys sample mean). If you have two multivariate distributions then there would be two such covariance matrices to compute or one pooled one if you assume the two distributions have the same covariance matrix.

share|improve this answer

Not the answer you're looking for? Browse other questions tagged or ask your own question.