Maximum Likelihood and Markov Chain Monte Carlo (MCMC) Methods for Pedigree Reconstruction and Analysis R package MasterBayes version 2.59 The primary aim of 'MasterBayes' is to use Markov chain Monte Carlo (MCMC) techniques to integrate over uncertainty in pedigree configurations estimated from molecular markers and phenotypic data (Hadfield et al. (2006) <doi:10.1111/j.1365-294X.2006.03050.x>). Emphasis is put on the marginal distribution of parameters that relate the phenotypic data to the pedigree. All simulation is done in compiled 'C++' for efficiency. Software Depends: coda, genetics, gtools, kinship2 Imports: methods, stats Jarrod Hadfield <j.hadfield@ed.ac.uk> Comprehensive R Archive Network (CRAN) Jarrod Hadfield [aut, cre], Andrew D. Martin [ctb, cph] (Original author of modified C++ Scythe code), Kevin M. Quinn [ctb, cph] (Original author of modified C++ Scythe code), Daniel Pemstein [ctb, cph] (Original author of modified C++ Scythe code) GPL (>= 2) 2026-03-19 application/tgz https://CRAN.R-project.org/package=MasterBayes doi:10.32614/CRAN.package.MasterBayes