smcPotts: Fit the hidden Potts model using approximate Bayesian computation with sequential Monte Carlo (ABC-SMC).
Description
Fit the hidden Potts model using approximate Bayesian computation with sequential Monte Carlo (ABC-SMC).
Usage
smcPotts(y, neighbors, blocks, param = list(npart = 10000, nstat = 50), priors = NULL)
Arguments
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.
Value
A matrix containing SMC samples for the parameters of the Potts model.