SwendsenWangAlg: Simulate a Potts model using the Swendsen-Wang algorithm

In ick003/SpTMixture: Mixture models with spatio-temporal dependencies

Description

This function allows you to simulate a Potts model using the Swendsen-Wang algorithm.

Usage

SwendsenWangAlg(beta, Coord = NULL, Neigh_Bonds = NULL, col.obs,
  Nrun = 10, sampling = "else")

Arguments

beta	parameters of the Potts model.
Coord	Matrix of coordinates.
col.obs	Binary matrix of colors.
Nrun	Number of MCMC runs.
sampling	Choice of sampling for the components.

References

Wang, J. and Swendsen, R. (1990) Cluster Monte Carlo algorithms. Physica A: Statistical Mechanics and its Applications 167 565–579.

Examples

beta = c(0.5,0.5,0.5)
Obs.loc = expand.grid(1:50,1:50)
id.pos = sample(1:3, 2500, replace = T)
Res20 = SwendsenWangAlg(beta, Coord = as.matrix(Obs.loc), col.obs = id.pos, Nrun = 20)
Res50 = SwendsenWangAlg(beta, Coord = as.matrix(Obs.loc), col.obs = id.pos, Nrun = 50)
Res500 = SwendsenWangAlg(beta, Coord = as.matrix(Obs.loc), col.obs = id.pos, Nrun = 500)
par(mfrow = c(2,2))
col = grey.colors(3)
image(matrix(Res20$col.old, ncol = 50), col = col)
image(matrix(Res20$col.new, ncol = 50), col = col)
image(matrix(Res50$col.new, ncol = 50), col = col)
image(matrix(Res500$col.new, ncol = 50), col = col)

ick003/SpTMixture documentation built on May 18, 2019, 2:32 a.m.