initSedki: Initialize the ABC algorithm using the method of Sedki et al....

In bayesImageS: Bayesian Methods for Image Segmentation using a Potts Model

Description

Initialize the ABC algorithm using the method of Sedki et al. (2013)

Usage

initSedki(y, neighbors, blocks, param = list(npart = 10000), priors = NULL)

Arguments

y	A vector of observed pixel data.
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.
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.

References

Sedki, M.; Pudlo, P.; Marin, J.-M.; Robert, C. P. & Cornuet, J.-M. (2013) "Efficient learning in ABC algorithms" arXiv:1210.1388

bayesImageS documentation built on April 11, 2021, 5:06 p.m.