7.2 Prove f in (7.6) maximizes the log likelihood (7.5) by minimizing the negative of the log likelihood

where the λi values correspond to the eigenvalues in a simultaneous diagonalization of the matrices f and ˆ f; i.e., there exists a matrix P such that P∗fP = I and P∗ fP = diag (λ1, . . . , λp) = Λ. Note, λi − ln λi − 1 ≥ 0 with equality if and only if λi = 1, implying Λ = I maximizes the log likelihood and f = f is the maximimizing value.

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in the form ( Lln f+Ltr {ff } L(A-In-1)+ Lp + L In|f], i