This repository contains the data and code used in the anlaysis of the results presented in the manuscript "Statistical Laws in Complex Systems", arXiv:2407.19874 (2024).

data/ datasets used in the analysis; Data on language needs to be downloaded from https://doi.org/10.5281/zenodo.13119897

notebooks/ Notebooks used to generate the figures of the paper

src/ source code used in the data analysis

This repository builds on the ideas, code, and data provided in previous work:

• Urban Scaling laws: Paper: J. C. Leitao, J.M. Miotto, M. Gerlach, and E. G. Altmann, "Is this scaling nonlinear?", Royal Society Open Science 3, 150649 (2016) Paper: E. G. Altmann, "Spatial interactions in urban scaling laws", PLOS ONE 15, e0243390 (2020) Code: https://github.com/edugalt/scaling

• Fitting frequency distributions and rank-frequency distributions Paper: M. Gerlach and E. G. Altmann, "Stochastic model for the vocabulary growth in natural languages", Phys. Rev. X 3, 021006 (2013) Paper: H. H. Chen, T. J. Alexander, D. F.M. Oliveira, E. G. Altmann, "Scaling laws and dynamics of hashtags on Twitter", Chaos 30, 063112 (2020) Code: https://github.com/edugalt/TwitterHashtags

• Effect of correlation Paper: M. Gerlach and E. G. Altmann, "Testing statistical laws in complex systems", Phys. Rev. Lett. 122, 168301 (2019) Code: https://github.com/martingerlach/testing-statistical-laws-in-complex-systems

• Constrained surrogates Paper: J. M. Moore, G. Yan, E. G Altmann, "Nonparametric Power-Law Surrogates", Phys. Rev. X 12, 021056 (2022) Codes: https://github.com/JackMurdochMoore/power-law/