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)
| y | A vector of observed pixel data. |
|---|---|
| neighbors | A matrix of all neighbors in the lattice, one row per pixel. |
| blocks | A list of pixel indices, dividing the lattice into independent blocks. |
| param | A list of options for the ABC-SMC algorithm. |
| priors | A list of priors for the parameters of the model. |
A matrix containing SMC samples for the parameters of the Potts model.