bn.fit, bn.fit.dnode and
bn.fit.gnode classes, based on the ## for Gaussian Bayesian networks.
bn.fit.qqplot(fitted, xlab = "Theoretical Quantiles",
ylab = "Sample Quantiles", main = "Normal Q-Q Plot", ...)
bn.fit.histogram(fitted, density = TRUE, xlab = "Residuals",
ylab = ifelse(density, "Density", ""),
main = "Histogram of the residuals", ...)
bn.fit.xyplot(fitted, xlab = "Fitted values",
ylab = "Residuals", main = "Residuals vs Fitted", ...)
## for discrete (multinomial and ordinal) Bayesian networks.
bn.fit.barchart(fitted, xlab = "Probabilities",
ylab = "Levels", main = "Conditional Probabilities", ...)
bn.fit.dotplot(fitted, xlab = "Probabilities",
ylab = "Levels", main = "Conditional Probabilities", ...)bn.fit, bn.fit.dnode
or bn.fit.gnode.TRUE the histogram is
plotted using relative frequencies, and the matching normal
density is added to the plot.source function), the return value must be printed
explicitly for the plot to be displayed.bn.fit.qqplot draws a quantile-quantile plot of the
residuals. bn.fit.histogram draws a histogram of the residuals,
using either absolute or relative frequencies.
bn.fit.xyplot plots the residuals versus the fitted
values.
bn.fit.barchart and bn.fit.dotplot plot
the probabilities in the conditional probability table
associated with each node.
bn.fit, bn.fit class.