How can I calculate the covariance matrix of a linear least-squares fit? How is this matrix defined?
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I know how to *use* the covariance matrix to get a confidence ellipse, and what its entries mean. I just don't know how you produce the matrix from the curve-fitting process in the first place.
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Answer:
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Other answers
Take your n by p observation matrix X. Covariance matrix C is: C = sigma^2(X^T*X) where sigma^2 is the estimated variance of the residuals r = y - Xb
Minh
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