# exactPotts

From bayesImageS v0.6-0
by Matt Moores

##### Calculate the distribution of the Potts model using a brute force algorithm.

**Warning**: this algorithm is O\((k^n)\) and therefore will not scale for
\(k^n > 2^{31} - 1\)

##### Usage

`exactPotts(neighbors, blocks, k, beta)`

##### Arguments

- neighbors
A matrix of all neighbours in the lattice, one row per pixel.

- blocks
A list of pixel indices, dividing the lattice into independent blocks.

- k
The number of unique labels.

- beta
The inverse temperature parameter of the Potts model.

##### Value

A list containing the following elements:

`expectation`

The exact mean of the sufficient statistic.

`variance`

The exact variance of the sufficient statistic.

`exp_PL`

Pseudo-likelihood (PL) approximation of the expectation of S(z).

`var_PL`

PL approx. of the variance of the sufficient statistic.

*Documentation reproduced from package bayesImageS, version 0.6-0, License: GPL (>= 2) | file LICENSE*

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