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Would help users actually see the references in the docstrings rather than having to go to the documentation site. See, e.g.,
log(A::AbstractMatrix)
If A has no negative real eigenvalue, compute the principal matrix logarithm of A, i.e.
the unique matrix X such that e^X = A and -\pi < Im(\lambda) < \pi for all the
eigenvalues \lambda of X. If A has nonpositive eigenvalues, a nonprincipal matrix
function is returned whenever possible.
If A is symmetric or Hermitian, its eigendecomposition (eigen) is used, if A is
triangular an improved version of the inverse scaling and squaring method is employed
(see [^AH12] and [^AHR13]). If A is real with no negative eigenvalues, then the real
Schur form is computed. Otherwise, the complex Schur form is computed. Then the upper
(quasi-)triangular algorithm in [^AHR13] is used on the upper (quasi-)triangular
factor.
│ [^AH12]
│
│ Awad H. Al-Mohy and Nicholas J. Higham, "Improved inverse scaling and
│ squaring algorithms for the matrix logarithm", SIAM Journal on Scientific
│ Computing, 34(4), 2012, C153-C169. doi:10.1137/110852553
│ (https://doi.org/10.1137/110852553)
│ [^AHR13]
│
│ Awad H. Al-Mohy, Nicholas J. Higham and Samuel D. Relton, "Computing the
│ Fréchet derivative of the matrix logarithm and estimating the condition
│ number", SIAM Journal on Scientific Computing, 35(4), 2013, C394-C410.
│ doi:10.1137/120885991 (https://doi.org/10.1137/120885991)Metadata
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documentationImprovements or additions to documentationImprovements or additions to documentation