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, ...)
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 is plotted using
relative frequencies, and the matching normal density is added to the plot.
additional arguments to be passed to lattice functions.
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.
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.