Plot functions for the 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, ...)
bn.fit.histogram(fitted, density = TRUE, xlab = "Residuals",
ylab = ifelse(density, "Density", ""), main, ...)
bn.fit.xyplot(fitted, xlab = "Fitted values", ylab = "Residuals", main, ...)
## for discrete (multinomial and ordinal) Bayesian networks.
bn.fit.barchart(fitted, xlab = "Probabilities", ylab = "Levels", main, ...)
bn.fit.dotplot(fitted, xlab = "Probabilities", ylab = "Levels", main, ...)
The lattice plot objects. Note that if auto-printing is turned off (for
example, when the code is loaded with the source function), the return
value must be printed explicitly for the plot to be displayed.
an object of class bn.fit, bn.fit.dnode or
bn.fit.gnode.
the label of the x axis, of the y axis, and the plot title.
a boolean value. If TRUE, the histogram uses relative
frequencies and shows the matching normal density.
additional arguments to be passed to lattice functions.
Marco Scutari
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.