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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>).

Versions across snapshots

VersionRepositoryFileSize
0.5-11 rolling linux/jammy R-4.5 potts_0.5-11.tar.gz 223.2 KiB
0.5-11 rolling linux/noble R-4.5 potts_0.5-11.tar.gz 223.6 KiB
0.5-11 rolling source/ R- potts_0.5-11.tar.gz 174.7 KiB
0.5-11 latest linux/jammy R-4.5 potts_0.5-11.tar.gz 223.2 KiB
0.5-11 latest linux/noble R-4.5 potts_0.5-11.tar.gz 223.6 KiB
0.5-11 latest source/ R- potts_0.5-11.tar.gz 174.7 KiB
0.5-11 2026-04-26 source/ R- potts_0.5-11.tar.gz 174.7 KiB
0.5-11 2026-04-23 source/ R- potts_0.5-11.tar.gz 174.7 KiB
0.5-11 2026-04-09 windows/windows R-4.5 potts_0.5-11.zip 229.6 KiB
0.5-11 2025-04-20 source/ R- potts_0.5-11.tar.gz 174.7 KiB

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