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

Description Usage Arguments Value See Also

View source: R/mcmcPotts.R

Description

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

Usage

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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.

See Also

mritc.bayes


bayesImageS documentation built on Nov. 17, 2017, 6:40 a.m.