We are given a set of n points that might be uniformly distributed in the unit square [0, 1] ².
We wish to test whether the set, although mostly consisting of uniformly scattered points,
also contains a small fraction of points sampled from some (a priori unknown) curve with
bounded by β. An asymptotic detection threshold exists in this problem; for a constant T_ (α,
β)> 0, if the number of points sampled from the curve is smaller than, reliable detection is not
possible for large n. We describe a multiscale significant-runs algorithm that can reliably …

We are given a set of n points that appears uniformly distributed in the unit square [0, 1] 2.
We wish to test whether the set actually is generated from a non-uniform distribution having
a small fraction of points concentrated on some (a priori unknown) curve with Cα-norm
bounded by β.