From: Feature analysis of multidisciplinary scientific collaboration patterns based on PNAS
Input: Observations \(D_{s}\) (s = 1,…,n), rescaling function g(⋅), and fitting model h(⋅). |
For k from 1 to \(\max(D_{1},\ldots,D_{n})\) do: |
Fit h(⋅) to the PDF \(h_{0}(\cdot)\) of \(\{D_{s}, s=1,\ldots,n|D_{s} \leq k\}\) by maximum-likelihood estimation; |
Do KS test for two data g(h(t)) and \(g( h_{0}(t))\), t = 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. |