Jeffreys.GBN {bnmonitor} | R Documentation |
GBN
Jeffreys.GBN
returns the Jeffreys divergence between an object of class GBN
and its update after a standard parameter variation.
## S3 method for class 'GBN' Jeffreys(x, where, entry, delta, ...)
x |
object of class |
where |
character string: either |
entry |
if |
delta |
numeric vector, including the variation parameters that act additively. |
... |
additional arguments for compatibility. |
Computation of the Jeffreys divergence between a Bayesian network and the additively perturbed Bayesian network, where the perturbation is either to the mean vector or to the covariance matrix.
A dataframe including in the first column the variations performed and in the second column the corresponding Jeffreys divergences.
Goergen, C., & Leonelli, M. (2018). Model-preserving sensitivity analysis for families of Gaussian distributions. arXiv preprint arXiv:1809.10794.
KL.GBN
KL.CI
, Fro.CI
, Fro.GBN
, Jeffreys.CI
Jeffreys(synthetic_gbn,"mean",2,seq(-1,1,0.1)) Jeffreys(synthetic_gbn,"covariance",c(3,3),seq(-1,1,0.1))