Tail fitting, quantile interpolation [14]

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Bullet points include: We re-express maximum likelihood to refer to the ordered observations: E.g. by writing the log-likelihood as: Instead of maximising log likelihood we maximise e.g. For some suitable weights, e.g. 1 if in tail, 0 otherwise. Allowing us to leverage intrinsic appeal of maximum likelihood estimation. Some subtleties if quantiles not equally spaced and complete

Bullet points include: We re-express maximum likelihood to refer to the ordered observations: E.g. by writing the log-likelihood as: Instead of maximising log likelihood we maximise e.g. For some suitable weights, e.g. 1 if in tail, 0 otherwise. Allowing us to leverage intrinsic appeal of maximum likelihood estimation. Some subtleties if quantiles not equally spaced and complete

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