Abstract
We construct minimum-width confidence bands with a predefined nominal coverage from a finite set of sample paths. In contrast to the several heuristics suggested in the literature, our mixed-integer optimization algorithm calculates global minimum-width pathwise confidence bands. For very large problems, our solution can be used as an approximation with a bounded and known gap to the globally optimal solution.
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