rmrf2d_mc: Markov Chain sampling of MRFs for Monte-Carlo methods

Description Usage Arguments Value Note Author(s) Examples

View source: R/rmrf.R

Description

Generates a Markov Chain of random fields and returns the sufficient statistics for each of the observations.

This function automatizes the process of generating a random sample of MRFs to be used in Monte-Carlo methods by wrapping rmrf2d and executing it multiple time while storing sufficient statistics instead of the entire lattice.

Usage

1
rmrf2d_mc(init_Z, mrfi, theta, family, nmc = 100, burnin = 100, cycles = 4)

Arguments

init_Z

One of two options:

  • A matrix object with the initial field configuration. Its valuesmust be integers in {0,...,C}.

  • A length 2 numeric vector with the lattice dimensions.

mrfi

A mrfi object representing the interaction structure.

theta

A 3-dimensional array describing potentials. Slices represent interacting positions, rows represent pixel values and columns represent neighbor values. As an example: theta[1,3,2] has the potential for the pair of values 0,2 observed in the second relative position of mrfi.

family

The family of parameter restrictions to potentials. Families are: 'onepar', 'oneeach', 'absdif', 'dif' or 'free'. See mrf2d-familiy.

nmc

Number of samples to be stored.

burnin

Number of cycles iterated before start collecting sufficient statistics.

cycles

Number of cycles between collected samples.

Value

A matrix where each row contains the vector of sufficient statistics for an observation.

Note

Fixed regions and incomplete lattices are not supported.

Author(s)

Victor Freguglia

Examples

1
rmrf2d_mc(c(80, 80), mrfi(1), theta_potts, family = "oneeach", nmc = 8)

mrf2d documentation built on Oct. 30, 2020, 1:07 a.m.