Additive Bayesian network models are equivalent to Bayesian multivariate regression using graphical modelling, they generalises the usual multivariable regression, GLM, to multiple dependent variables. An additive Bayesian network model consists of a form of a DAG where each node comprises a generalized linear model, GLM. Modelling Multivariate Data with Additive Bayesian Networksīayesian network analysis is a form of probabilistic graphical models which derives from empirical data a directed acyclic graph, DAG, describing the dependency structure between random variables. Cross-validation tools are also available for measuring the accuracy of ABC estimates, and to calculate the misclassification probabilities of different models. Implements several ABC algorithms for performing parameter estimation, model selection, and goodness-of-fit. Tools for Approximate Bayesian Computation (ABC)
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