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Mar 11, 2015 at 23:55 answer added Artem Sobolev timeline score: 3
Mar 4, 2015 at 0:15 comment added Hirek Your last equality is not clear to me. Why is Sigma inverse equal to A'A? But the thing is that the selected matrix norm will correspond to the largest eigenvalue which means you're looking at a likelihood-type maximization problem. Note that max b'A'Ab will be the largest eigenvalue of A'A if you pick b as eigenvectors belonging to the largest eigenvalue and normalizing them such that b'b = 1. However, are you positive that the vector x is included in the matrix norm? Your problem sounds intriguing but give us a little more context.
Mar 3, 2015 at 23:45 comment added amoeba OK, if it's about interpretation of A (rather than getting a formula for A), then I agree with @user603 that it belongs here. Your original formulation was about "significance of A" and that was not very clear.
Mar 3, 2015 at 23:14 history edited amoeba CC BY-SA 3.0
clarified the question
Mar 3, 2015 at 23:02 comment added user1943079 I would still like to get an intuitive understanding of what matrix A means
Mar 3, 2015 at 22:57 review Close votes
Mar 3, 2015 at 23:49
Mar 3, 2015 at 22:55 comment added user603 This is a good forum for this question.
Mar 3, 2015 at 22:39 history edited amoeba CC BY-SA 3.0
light editing
Mar 3, 2015 at 22:37 comment added amoeba Also, can you comment on how this question is connected to statistics? I am voting to migrate it to mathematics SE.
Mar 3, 2015 at 22:35 comment added amoeba Following your previous comment: Have you already solved the problem, or do you still need help?
Mar 3, 2015 at 19:03 comment added user1943079 Yep, just figured it out to be $\frac{1}{\sqrt{\lambda}}$ where $\lambda$ is the eigenvalues of the covariance matrix
Mar 3, 2015 at 15:16 comment added Brian Borchers Can you figure out the square root of $\Lambda^{-1}$? Do you know what $Q^{-1}$ inverse is?
Mar 3, 2015 at 1:14 history asked user1943079 CC BY-SA 3.0