Search Results for author:
Found 5 papers, 0 papers with code
Additive Bayesian Network Modelling with the R Package abn
The R package abn is designed to fit additive Bayesian models to observational datasets.
Is a single unique Bayesian network enough to accurately represent your data?
Unfortunately, they essentially all rely on very crude decisions that result in too simplistic approaches for such complex systems.
Comparison between Suitable Priors for Additive Bayesian Networks
The second prior belongs to the Student's t-distribution, specifically designed for logistic regressions and, finally, the strongly informative prior is again Gaussian with mean equal to true parameter value and a small variance.
Information-Theoretic Scoring Rules to Learn Additive Bayesian Network Applied to Epidemiology
Bayesian network modelling is a well adapted approach to study messy and highly correlated datasets which are very common in, e. g., systems epidemiology.
varrank: an R package for variable ranking based on mutual information with applications to observed systemic datasets
This article describes the R package varrank.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
