Skip to contents

R port of morie.tps_statphysics. Implements the four canonical methods reviewed by D'Orsogna & Perc (2015), Statistical physics of crime: A review, Physics of Life Reviews 12: 1-21 (arXiv:1411.1743), together with two illustrative companions (canonical Turing-pattern demo and Helbing-Szolnoki inspection-game phase diagram) and a premise x neighbourhood co-occurrence network.

Details

Each callable consumes one TPS category and returns a multi-section morie_rich_result. Cosine-corrected projection and DBSCAN delegation are deferred to companion modules (tps_render, tps_spatial_advanced); when those collaborators are not available the routines fall back to a stop-stub explaining the gap.

Functions

References

D'Orsogna MR, Perc M (2015). Statistical physics of crime: A review. Physics of Life Reviews 12: 1-21.

Short MB, D'Orsogna MR, Pasour VB, Tita GE, Brantingham PJ, Bertozzi AL, Chayes LB (2008). A statistical model of criminal behavior. Mathematical Models and Methods in Applied Sciences 18(supp01): 1249-1267.

Brockmann D, Hufnagel L, Geisel T (2006). The scaling laws of human travel. Nature 439: 462-465.

Bettencourt LMA, Lobo J, Helbing D, Kuhnert C, West GB (2007). Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences 104: 7301-7306.

Helbing D, Szolnoki A, Perc M, Szabo G (2010). Punish, but not too hard: how costly punishment spreads in the spatial public goods game. New Journal of Physics 12: 083005.

Diviak T, Dijkstra JK, Snijders TAB (2019). Structure, multiplexity, and centrality in a corruption network. Trends in Organized Crime 22: 274-297.