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 burnin. 
... 
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