| mean_var {bnmonitor} | R Documentation |
Standard variation of the mean vector
Description
Computation of an updated GBN object after a variation of the mean vector.
Usage
mean_var(gbn, entry, delta)
Arguments
gbn |
object of class |
entry |
an index specifying the entry of the mean vector to vary. |
delta |
additive variation coefficient for the entry of the mean vector given in |
Details
Let the original Bayesian network have a Normal distribution \mathcal{N}(\mu,\Sigma) and let entry be equal to i. Let \mu_i be the i-th entry of \mu. For a variation of the mean by an amount \delta the resulting distribution is \mathcal{N}(\mu',\Sigma), where \mu' is equal to \mu except for the i-th entry which is equal to \mu+\delta.
Value
An object of class GBN with an updated mean vector.
References
Gómez-Villegas, M. A., Maín, P., & Susi, R. (2007). Sensitivity analysis in Gaussian Bayesian networks using a divergence measure. Communications in Statistics—Theory and Methods, 36(3), 523-539.
Gómez-Villegas, M. A., Main, P., & Susi, R. (2013). The effect of block parameter perturbations in Gaussian Bayesian networks: Sensitivity and robustness. Information Sciences, 222, 439-458.
See Also
Examples
mean_var(synthetic_gbn,2,3)