MoTBFs: An R Package for Learning Hybrid Bayesian Networks Using Mixtures of Truncated Basis Functions

Pérez-Bernabé, Inmaculada; Maldonado, Ana D.; Salmerón, Antonio; Nielsen, Thomas D.

doi:10.32614/rj-2021-019

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MoTBFs: An R Package for Learning Hybrid Bayesian Networks Using Mixtures of Truncated Basis Functions

Cited by 4 publications

References 4 publications

Probabilistic Graphical Models with Continuous Variables for the Decision Making About Risky Episodic Behavior in the Framework of Gamma Poisson Model with Application to Public Posting Data

Probabilistic Graphical Models with Continuous Variables for the Decision Making About Risky Episodic Behavior in the Framework of Gamma Poisson Model with Application to Public Posting Data

Modernising operational risk management in financial institutions via data-driven causal factors analysis: A pre-registered report

Approaches to Accounting for the Uncertainty of Data on the Time of Realization of Episodes in Models for Assessing the Characteristics of Individuals Episodic Behavior

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