Fit the hidden Potts model using approximate Bayesian computation with sequential Monte Carlo (ABC-SMC).
smcPotts(y, neighbors, blocks, param = list(npart = 10000, nstat = 50),
priors = NULL)
A vector of observed pixel data.
A matrix of all neighbors in the lattice, one row per pixel.
A list of pixel indices, dividing the lattice into independent blocks.
A list of options for the ABC-SMC algorithm.
A list of priors for the parameters of the model.
A matrix containing SMC samples for the parameters of the Potts model.