smcPotts {bayesImageS} | R Documentation |

## 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.

[Package

*bayesImageS*version 0.6-1 Index]