In the simple linear model setting with (mu in mathcal{X}) and (Sigma propto I_{n}), show that the
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In the simple linear model setting with \(\mu \in \mathcal{X}\) and \(\Sigma \propto I_{n}\), show that the maximum value of the \(\log\) likelihood is const \(-n \log \|Q Y\|\), where \(Q=I-P\) is the orthogonal projection with kernel \(\mathcal{X}\), and the constant is independent of \(\mathcal{X}\).
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