From: Feature analysis of multidisciplinary scientific collaboration patterns based on PNAS
Input: Data vector \(h_{0}(s)\) (s = 1,…,K), rescaling function g(⋅), and fitting model h(⋅). |
For k from 1 to K do: |
Fit h(⋅) to \(h_{0}(s)\), s = 1,…,k by regression; |
Do KS test for two data vectors g(h(s)) and \(g( h_{0}(s))\), s = 1,…,k with the null hypothesis they coming from the same distribution; |
Break if the test rejects the null hypothesis at significance level 5%. |
Output: The current k as the boundary point. |