7. Cluster radius estimationΒΆ


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We begin by counting the number of RDP points that fall below a given maximum tolerance interval above \(d_{field}\). When the number of these points reaches a fixed value, \(n_{fixed}\), the point closest to \(d_{field}\) is stored as the most probable radius for this iteration. This process is repeated increasing the tolerance around \(d_{field}\) which results in another probable radius being stored, not necessarily the same found in the previous iteration. The final estimation for \(r_{cl}\) and its associated error comes from averaging the set of radius values stored this way and taking its standard deviation, respectively.