mcmcPotts {bayesImageS} | R Documentation |

## 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.

[Package

*bayesImageS*version 0.6-1 Index]