plot.BayesNnet {BoomSpikeSlab} | R Documentation |
Plot a Bayesian Neural Network
Description
The default plot is a barplot of the marginal inclusion probabilities
for each variable, as obtained by
PlotMarginalInclusionProbabilities
. Other interesting
plots can be obtained by supplying a string as the second argument.
Usage
## S3 method for class 'BayesNnet'
plot(x,
y = c("predicted", "residual", "structure", "partial", "help"),
...)
PlotBayesNnetPredictions(model, burn = SuggestBurn(model), ...)
PlotBayesNnetResiduals(model, burn = SuggestBurn(model), ...)
PlotNetworkStructure(model, ...)
Arguments
model |
An object of class |
x |
An object of class |
y |
The type of plot desired, or the name of the variable to plot
against. The name If
If |
burn |
The number of MCMC iterations to discard as burn-in. |
... |
Additional arguments passed to the specific functions
that do the plotting. For residual and predicted plots that is the
|
Details
Residual and predicted plots should be self explanatory. The network structure plot is fairly standard for neural network models. The width of a line linking two nodes is determined by the absolute value of the corresponding coefficient.
Author(s)
Steven L. Scott
See Also
BayesNnet
PartialDependencePlot
Examples
## See the examples in ?BayesNnet