GDAGsim is a software library which can be used to carry out conditional sampling of linear Gaussian directed acyclic graph models, and hence can be used for the implementation of efficient block MCMC samplers for such models. This paper examines the software library and its design, and how it can be applied to problems in Bayesian inference.
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