5 papers
Estimating Staged Event Tree Models via Hierarchical Clustering on the Simplex
Muhammad Shoaib, Eva Riccomagno, Manuele Leonelli +1
Staged tree models enhance Bayesian networks by incorporating context-specific dependencies through a stage-based structure. In this study, we present a new framework for estimatin…
Markov Combinations of Discrete Statistical Models
Orlando Marigliano, Eva Riccomagno
Markov combination is an operation that takes two statistical models and produces a third whose marginal distributions include those of the original models. Building upon and exten…
Learning Staged Trees from Incomplete Data
Jack Storror Carter, Manuele Leonelli, Eva Riccomagno +1
Staged trees are probabilistic graphical models capable of representing any class of non-symmetric independence via a coloring of its vertices. Several structural learning routines…
Data-Driven Strategies for Detecting and Sampling Misrepresented Subgroups
G. Lancia, F. Mecatti, E. Riccomagno
Economic policy research frequently examines population well-being, with a particular focus on the relationships between unequal living conditions, low educational attainment, and…
Staged trees for discrete longitudinal data
Jack Storror Carter, Manuele Leonelli, Eva Riccomagno +1
In this paper we investigate the use of staged tree models for discrete longitudinal data. Staged trees are a type of probabilistic graphical model for finite sample space processe…