mcmcPotts {bayesImageS}

Fit the hidden Potts model using a Markov chain Monte Carlo algorithm.

Description

Fit the hidden Potts model using a Markov chain Monte Carlo algorithm.

Usage

mcmcPotts(
  y,
  neighbors,
  blocks,
  priors,
  mh,
  niter = 55000,
  nburn = 5000,
  truth = 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.

priors

A list of priors for the parameters of the model.

mh

A list of options for the Metropolis-Hastings algorithm.

niter

The number of iterations of the algorithm to perform.

nburn

The number of iterations to discard as burn-in.

truth

A matrix containing the ground truth for the pixel labels.

Value

A matrix containing MCMC samples for the parameters of the Potts model.