gibbsPotts {bayesImageS} | R Documentation |
Fit a hidden Potts model to the observed data, using a fixed value of beta.
gibbsPotts(y, labels, beta, mu, sd, neighbors, blocks, priors, niter = 1)
y |
A vector of observed pixel data. |
labels |
A matrix of pixel labels. |
beta |
The inverse temperature parameter of the Potts model. |
mu |
A vector of means for the mixture components. |
sd |
A vector of standard deviations for the mixture components. |
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. |
niter |
The number of iterations of the algorithm to perform. |
A matrix containing MCMC samples for the parameters of the Potts model.