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Frobenius norm for GBN

Source: R/frobenius.R
Fro.GBN.Rd

Fro.GBN returns the Frobenius norm between between an object of class GBN and its update after a standard parameter variation.

Usage

# S3 method for GBN
Fro(x, entry, delta, log = TRUE, ...)

Arguments

x

object of class GBN.

entry

a vector of length 2 indicating the entry of the covariance matrix to vary.

delta

numeric vector, including the variation parameters that act additively.

log

boolean value. If TRUE, the logarithm of the Frobenius norm is returned. Set by default to TRUE.

...

additional arguments for compatibility.

Value

A dataframe including in the first column the variations performed and in the second column the corresponding Frobenius norm.

Details

Computation of the Frobenius norm between a Bayesian network and the additively perturbed Bayesian network, where the perturbation is either to the mean vector or to the covariance matrix. The Frobenius norm is not computed for perturbations of the mean since it is always equal to zero.

See also

KL.GBN, KL.CI, Fro.CI, Jeffreys.GBN, Jeffreys.CI

Examples

Fro(synthetic_gbn,c(3,3),seq(-1,1,0.1))
#>    Variation  Frobenius
#> 1       -1.0         NA
#> 2       -0.9         NA
#> 3       -0.8         NA
#> 4       -0.7         NA
#> 5       -0.6         NA
#> 6       -0.5         NA
#> 7       -0.4         NA
#> 8       -0.3         NA
#> 9       -0.2 -3.2188758
#> 10      -0.1 -4.6051702
#> 11       0.0       -Inf
#> 12       0.1 -4.6051702
#> 13       0.2 -3.2188758
#> 14       0.3 -2.4079456
#> 15       0.4 -1.8325815
#> 16       0.5 -1.3862944
#> 17       0.6 -1.0216512
#> 18       0.7 -0.7133499
#> 19       0.8 -0.4462871
#> 20       0.9 -0.2107210
#> 21       1.0  0.0000000