bnmonitor {bnmonitor}R Documentation

bnmonitor: A package for sensitivity analysis and robustness in Bayesian networks


Sensitivity and robustness analysis for Bayesian networks.


bnmonitor provides functions to perform sensitivity analysis for both discrete Bayesian networks (DBNs) and Gaussian Bayesian networks (GBNs).

In the discrete case, it provides three categories of functions: co-variation schemes, dissimilarity measures and sensitivity related functions.

In the continuous case, both standard and model-preserving methods are available for perturbation of the mean vector and the co-variance matrix.

bnmonitor further provides function to perform robustness studies in DBNs to verify how well a network fits a specific dataset.

DBNs - Robustness

The available functions for robustness are:

DBNs - Co-variation schemes

The available co-variation schemes are:

DBNs - Dissimilarity measures

The dissimilarity measures quantify the difference between a Bayesian network and its update after parameter variation.
The available dissimilarity measures are:

DBNs - Sensitivity functions

The available functions for sensitivity analysis are:

GBNs - Model-Preserving matrices

The available functions to construct model-preserving co-variation matrices are:

GBNs - Mean and Covariance variations

The available functions to perturb the distribution of a GBN are:

GBNs - Dissimilarity measures

The available dissimilarity measures are:

[Package bnmonitor version 0.1.4 Index]