Other packages > Find by keyword >

bayesImageS  

Bayesian Methods for Image Segmentation using a Potts Model
View on CRAN: Click here


Download and install bayesImageS package within the R console
Install from CRAN:
install.packages("bayesImageS")

Install from Github:
library("remotes")
install_github("cran/bayesImageS")

Install by package version:
library("remotes")
install_version("bayesImageS", "0.7-0")



Attach the package and use:
library("bayesImageS")
Maintained by
Matt Moores
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-11-03
Latest Update: 2021-04-11
Description:
Various algorithms for segmentation of 2D and 3D images, such as computed tomography and satellite remote sensing. This package implements Bayesian image analysis using the hidden Potts model with external field prior of Moores et al. (2015) . Latent labels are sampled using chequerboard updating or Swendsen-Wang. Algorithms for the smoothing parameter include pseudolikelihood, path sampling, the exchange algorithm, approximate Bayesian computation (ABC-MCMC and ABC-SMC), and the parametric functional approximate Bayesian (PFAB) algorithm. Refer to for an overview and also to and for further details of specific algorithms.
How to cite:
Matt Moores (2016). bayesImageS: Bayesian Methods for Image Segmentation using a Potts Model. R package version 0.7-0, https://cran.r-project.org/web/packages/bayesImageS. Accessed 15 Jul. 2026.
Previous versions and publish date:
(2026-07-09 07:20), 0.3-3 (2016-11-03 20:27), 0.4-0 (2017-03-21 16:13), 0.4-1 (2017-10-19 19:44), 0.5-0 (2018-01-26 16:28), 0.5-1 (2018-02-02 17:32), 0.5-2 (2018-06-07 15:51), 0.5-3 (2018-08-30 07:35), 0.6-0 (2019-01-04 12:20), 0.6-1 (2021-04-11 17:10), 0.7-0 (2025-10-10 10:30)
Other packages that cited bayesImageS R package
View bayesImageS citation profile
Other R packages that bayesImageS depends, imports, suggests or enhances
Complete documentation for bayesImageS
Functions, R codes and Examples using the bayesImageS R package
Some associated functions: bayesImageS . exactPotts . getBlocks . getEdges . getNeighbors . gibbsGMM . gibbsNorm . gibbsPotts . initSedki . mcmcPotts . mcmcPottsNoData . res . res2 . res3 . res4 . res5 . smcPotts . sufficientStat . swNoData . synth . testResample . 
Some associated R codes: bayesImageS.R . data.R . getBlocks.R . getEdges.R . getNeighbors.R . mcmcPotts.R . smcPotts.R .  Full bayesImageS package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  
footBayes  
Fitting Bayesian and MLE Football Models
This is the first package allowing for the estimation, visualization and prediction of the most wel ...
Download / Learn more Package Citations See dependency  
gscaLCA  
Generalized Structure Component Analysis- Latent Class Analysis & Latent Class Regression
Execute Latent Class Analysis (LCA) and Latent Class Regression (LCR) by using Generalized Structu ...
Download / Learn more Package Citations See dependency  
gamlss.add  
Extra Additive Terms for Generalized Additive Models for Location Scale and Shape
Interface for extra smooth functions including tensor products, neural networks and decision trees. ...
Download / Learn more Package Citations See dependency  
PermAlgo  
Permutational Algorithm to Simulate Survival Data
This version of the permutational algorithm generates a dataset in which event and censoring times ...
Download / Learn more Package Citations See dependency  
binhf  
Haar-Fisz Functions for Binomial Data
Binomial Haar-Fisz transforms for Gaussianization as in Nunes and Nason (2009). ...
Download / Learn more Package Citations See dependency  

27,806

R Packages

239,283

Dependencies

73,837

Author Associations

27,807

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA