exactPotts

0th

Percentile

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 neighbors 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.

Aliases
  • exactPotts
Documentation reproduced from package bayesImageS, version 0.4-0, License: GPL (>= 2)

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