bn.fit, bn.fit.dnode and
  bn.fit.gnode classes, based on the lattice package.## 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.