By Jami Mulgrave and Subhashis Ghosal

A nonparanormal graphical model is a semiparametric generalization of a Gaussian graphical model for continuous variables in which it is assumed that the variables follow a Gaussian graphical model only after some unknown smooth monotone transformations. We consider a Bayesian approach to inference in a nonparanormal graphical model in which... Show more

February 20, 2021

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Regression-Based Bayesian Estimation and Structure Learning for Nonparanormal Graphical Models

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