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math.ST2021★ 2 cited
Markov Equivalence of Max-Linear Bayesian Networks
Carlos Améndola, Ben Hollering, Seth Sullivant +1
Max-linear Bayesian networks have emerged as highly applicable models for causal inference via extreme value data. However, conditional independence (CI) for max-linear Bayesian ne…
math.ST2021★ 1 cited
Discrete Max-Linear Bayesian Networks
Benjamin Hollering, Seth Sullivant
Discrete max-linear Bayesian networks are directed graphical models specified by the same recursive structural equations as max-linear models but with discrete innovations. When al…