Context-specific independencies in stratified chain regression graphical models

DOI10.3150/20-BEJ1302zbMath1477.62154MaRDI QIDQ2040108

Federica Nicolussi, Manuela Cazzaro

Publication date: 9 July 2021

Published in: Bernoulli (Search for Journal in Brave)

zbMATH Keywords

graphical modelscategorical variablesmarginal modelsmultivariate regression modelsstratified Markov properties

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) General nonlinear regression (62J02) Contingency tables (62H17) Probabilistic graphical models (62H22)

Uses Software

• R
• hmmm

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Context-specific independence in graphical log-linear models
• Type II chain graph models for categorical data: a smooth subclass
• Discrete chain graph models
• Chain graph models of multivariate regression type for categorical data
• Modelling two way contingency tables with recursive logits and odds ratios
• Split models for contingency tables
• Linear dependencies represented by chain graphs. With comments and a rejoinder by the authors
• Labeled directed acyclic graphs: a generalization of context-specific independence in directed graphical models
• Unifying Markov properties for graphical models
• Marginal models for categorical data
• Ancestral graph Markov models.
• Context-specific independencies in hierarchical multinomial marginal models
• Markov properties for mixed graphs
• Marginal Nested Interactions for Contingency Tables
• Marginal log-linear parameterization of conditional independence models
• Maximum-Likelihood Estimation of Parameters Subject to Restraints
• Context-Specific Independencies Embedded in Chain Graph Models of Type I
• Joint Response Graphs and Separation Induced by Triangular Systems
• Statistical Inference in Context Specific Interaction Models for Contingency Tables
• Context-Specific and Local Independence in Markovian Dependence Structures
• Graphical Models for Categorical Data

This page was built for publication: Context-specific independencies in stratified chain regression graphical models