Package: potts 0.5-11

potts: Markov Chain Monte Carlo for Potts Models

Do Markov chain Monte Carlo (MCMC) simulation of Potts models (Potts, 1952, <doi:10.1017/S0305004100027419>), which are the multi-color generalization of Ising models (so, as as special case, also simulates Ising models). Use the Swendsen-Wang algorithm (Swendsen and Wang, 1987, <doi:10.1103/PhysRevLett.58.86>) so MCMC is fast. Do maximum composite likelihood estimation of parameters (Besag, 1975, <doi:10.2307/2987782>, Lindsay, 1988, <doi:10.1090/conm/080>).

Authors:Charles J. Geyer <[email protected]> and Leif Johnson <[email protected]>

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potts.pdf |potts.html✨
potts/json (API)
NEWS

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23 exports 0.00 score 0 dependencies 30 scripts 416 downloads

Last updated 2 years agofrom:364fd58828. Checks:OK: 9. Indexed: yes.

Exports:calc_tcalc_t_fullcalc_t_innergridcomposite.llfourpixelfourpixel.nonoverlapgenerate_t_cachegenfourbyfourgenfourpixelgengridcachegensingletongenthreebythreegentwopixelgr.composite.llinspectPottsninepixel.nonoverlappackPottspottssingletonsixteenpixel.nonoverlaptwopixeltwopixel.nonoverlapunpackPotts

Dependencies: