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 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
.