The R Package stagedtrees for Structural Learning of Stratified Staged Trees
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Abstract (arXiv)
stagedtrees is an R package which includes several algorithms for learning the structure of staged trees and chain event graphs from data. Score-based and clustering-based algorithms are implemented, as well as various functionalities to plot the models and perform inference. The capabilities of stagedtrees are illustrated using mainly two datasets both included in the package or bundled in R.
Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Apr 2020.
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Citing papers per year: 2021: 3; 2022: 4; 2023: 2; 2024: 4; 2025: 3; 2026: 1.
17 papers.
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- 2025Extracting Probabilistic Knowledge from Large Language Models for Bayesian Network Parameterizationcited by 15
- 2021Context-Specific Causal Discovery for Categorical Data Using Staged Treescited by 10
- 2021Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R packagecited by 8
- 2021Staged trees and asymmetry-labeled DAGscited by 8
- 2022Structural Learning of Simple Staged Treescited by 7
- 2022Highly Efficient Structural Learning of Sparse Staged Treescited by 6
- 2022cegpy: Modelling with Chain Event Graphs in Pythoncited by 3
- 2023Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fearcited by 2
- 2023The YODO algorithm: An efficient computational framework for sensitivity analysis in Bayesian networkscited by 2
- 2024Learning Staged Trees from Incomplete Datacited by 1
- 2024The diameter of a stochastic matrix: A new measure for sensitivity analysis in Bayesian networkscited by 1
- 2022Beyond Conjugacy for Chain Event Graph Model Selectioncited by 0
5 more
- 2024Scalable Structure Learning for Sparse Context-Specific Systemscited by 0
- 2024Context-Specific Refinements of Bayesian Network Classifierscited by 0
- 2025stCEG: An R Package for Modelling Events over Spatial Areas Using Chain Event Graphscited by 0
- 2025Staged Event Trees for Transparent Treatment Effect Estimationcited by 0
- 2026Estimating Staged Event Tree Models via Hierarchical Clustering on the Simplexcited by 0
- 2026Estimating Staged Event Tree Models via Hierarchical Clustering on the Simplex16 Mar 2026
- 2025Staged Event Trees for Transparent Treatment Effect Estimation30 Sep 2025
- 2025stCEG: An R Package for Modelling Events over Spatial Areas Using Chain Event Graphs9 Jul 2025
- 2025Extracting Probabilistic Knowledge from Large Language Models for Bayesian Network Parameterization21 May 2025
- 2024The diameter of a stochastic matrix: A new measure for sensitivity analysis in Bayesian networks5 Jul 2024
- 2024Learning Staged Trees from Incomplete Data28 May 2024
- 2024Context-Specific Refinements of Bayesian Network Classifiers28 May 2024
- 2024Scalable Structure Learning for Sparse Context-Specific Systems12 Feb 2024
- 2023The YODO algorithm: An efficient computational framework for sensitivity analysis in Bayesian networks1 Feb 2023
- 2023Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear2 Jan 2023
- 2022cegpy: Modelling with Chain Event Graphs in Python21 Nov 2022
- 2022Beyond Conjugacy for Chain Event Graph Model Selection7 Nov 2022
5 more
- 2022Highly Efficient Structural Learning of Sparse Staged Trees14 Jun 2022
- 2022Structural Learning of Simple Staged Trees8 Mar 2022
- 2021Staged trees and asymmetry-labeled DAGs4 Aug 2021
- 2021Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R package25 Jul 2021
- 2021Context-Specific Causal Discovery for Categorical Data Using Staged Trees8 Jun 2021
- 2025Extracting Probabilistic Knowledge from Large Language Models for Bayesian Network Parameterizationcited by 15
- 2021Context-Specific Causal Discovery for Categorical Data Using Staged Treescited by 10
- 2021Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R packagecited by 8
- 2021Staged trees and asymmetry-labeled DAGscited by 8
- 2022Structural Learning of Simple Staged Treescited by 7
- 2022Highly Efficient Structural Learning of Sparse Staged Treescited by 6
- 2022cegpy: Modelling with Chain Event Graphs in Pythoncited by 3
- 2023Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fearcited by 2
- 2023The YODO algorithm: An efficient computational framework for sensitivity analysis in Bayesian networkscited by 2
- 2024Learning Staged Trees from Incomplete Datacited by 1
- 2024The diameter of a stochastic matrix: A new measure for sensitivity analysis in Bayesian networkscited by 1
- 2022Beyond Conjugacy for Chain Event Graph Model Selectioncited by 0
12 most cited of 17 All 17 (JSON)
- 2026Estimating Staged Event Tree Models via Hierarchical Clustering on the Simplex16 Mar 2026
- 2025Staged Event Trees for Transparent Treatment Effect Estimation30 Sep 2025
- 2025stCEG: An R Package for Modelling Events over Spatial Areas Using Chain Event Graphs9 Jul 2025
- 2025Extracting Probabilistic Knowledge from Large Language Models for Bayesian Network Parameterization21 May 2025
- 2024The diameter of a stochastic matrix: A new measure for sensitivity analysis in Bayesian networks5 Jul 2024
- 2024Learning Staged Trees from Incomplete Data28 May 2024
- 2024Context-Specific Refinements of Bayesian Network Classifiers28 May 2024
- 2024Scalable Structure Learning for Sparse Context-Specific Systems12 Feb 2024
- 2023The YODO algorithm: An efficient computational framework for sensitivity analysis in Bayesian networks1 Feb 2023
- 2023Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear2 Jan 2023
- 2022cegpy: Modelling with Chain Event Graphs in Python21 Nov 2022
- 2022Beyond Conjugacy for Chain Event Graph Model Selection7 Nov 2022
12 newest of 17 All 17 (JSON)