bn.fit plots {bnlearn} | R Documentation |
Plots related to 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 = "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", ...)
fitted |
an object of class bn.fit , bn.fit.dnode
or bn.fit.gnode . |
xlab, ylab, main |
the label of the x axis, of the y axis, and the plot title. |
density |
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. |
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.
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.
Marco Scutari