Bayesian learning of multiple directed networks from observational data
Article Properties
-
LanguageEnglish
-
DOI (url)
-
Publication Date2020/09/23
-
Journal
-
Indian UGC (journal)
-
Refrences49
-
Citations9
-
Federico Castelletti Department of Statistical Sciences Università Cattolica del Sacro Cuore Milan Italy
-
Luca La Rocca Department of Physics, Informatics and Mathematics Università degli Studi di Modena e Reggio Emilia Modena Italy
-
Stefano Peluso Department of Statistical Sciences Università Cattolica del Sacro Cuore Milan Italy
-
Francesco C. Stingo Department of Statistics, Computer Science, Applications “G. Parenti” Università degli Studi di Firenze Florence Italy ORCID (unauthenticated)
-
Guido Consonni Department of Statistical Sciences Università Cattolica del Sacro Cuore Milan Italy
Abstract
Cite
Castelletti, Federico, et al. “Bayesian Learning of Multiple Directed Networks from Observational Data”. Statistics in Medicine, vol. 39, no. 30, 2020, pp. 4745-66, https://doi.org/10.1002/sim.8751.
Castelletti, F., La Rocca, L., Peluso, S., Stingo, F. C., & Consonni, G. (2020). Bayesian learning of multiple directed networks from observational data. Statistics in Medicine, 39(30), 4745-4766. https://doi.org/10.1002/sim.8751
Castelletti, Federico, Luca La Rocca, Stefano Peluso, Francesco C. Stingo, and Guido Consonni. “Bayesian Learning of Multiple Directed Networks from Observational Data”. Statistics in Medicine 39, no. 30 (2020): 4745-66. https://doi.org/10.1002/sim.8751.
Castelletti F, La Rocca L, Peluso S, Stingo FC, Consonni G. Bayesian learning of multiple directed networks from observational data. Statistics in Medicine. 2020;39(30):4745-66.
Journal Categories
Medicine
Internal medicine
Special situations and conditions
Industrial medicine
Industrial hygiene
Medicine
Medicine (General)
Medicine
Medicine (General)
Computer applications to medicine
Medical informatics
Medicine
Medicine (General)
Medical technology
Science
Biology (General)
Science
Mathematics
Probabilities
Mathematical statistics
Social Sciences
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Learning Markov equivalence classes of directed acyclic graphs: an objective Bayes approach | Bayesian Analysis | 2018 | ||
| Phosphorylation of GSK3α/β correlates with activation of AKT and is prognostic for poor overall survival in acute myeloid leukemia patients | BBA Clinical | 32 | 2015 | |
| Objective Bayes model selection of Gaussian interventional essential graphs for the identification of signaling pathways | The Annals of Applied Statistics |
| 2019 | |
| Hierarchical normalized completely random measures for robust graphical modeling | Bayesian Analysis | 2018 | ||
| Bayesian graphical models for differential pathways | Bayesian Analysis | 2016 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Learning Block Structured Graphs in Gaussian Graphical Models | Journal of Computational and Graphical Statistics |
| 2023 | |
| Bayesian Multi-Task Variable Selection with an Application to Differential DAG Analysis | Journal of Computational and Graphical Statistics |
| 2023 | |
Using Bayesian networks with tabu algorithm to explore factors related to chronic kidney disease with mental illness: A cross-sectional study | Mathematical Biosciences and Engineering | 2023 | ||
Foreign Language Anxiety of College English Teachers and Their Countermeasures | International Journal of Cognitive Informatics and Natural Intelligence |
| 2023 | |
Bayesian graphical modeling for heterogeneous causal effects | Statistics in Medicine |
| 1 | 2022 |
Citations Analysis
The category
Science: Mathematics: Probabilities. Mathematical statistics 6
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Equivalence class selection of categorical graphical models and was published in 2021. The most recent citation comes from a 2023 study titled Foreign Language Anxiety of College English Teachers and Their Countermeasures. This article reached its peak citation in 2023, with 4 citations. It has been cited in 8 different journals. Among related journals, the Journal of Computational and Graphical Statistics cited this research the most, with 2 citations. The chart below illustrates the annual citation trends for this article.