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bn.fit plots {bnlearn} | R Documentation |
Plot fitted Bayesian networks
Description
Plot functions for the bn.fit
, bn.fit.dnode
and bn.fit.gnode
classes, based on the lattice package.
Usage
## 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, ...)
Arguments
fitted |
an object of class |
xlab, ylab, main |
the label of the x axis, of the y axis, and the plot title. |
density |
a boolean value. If |
... |
additional arguments to be passed to lattice functions. |
Details
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.
Value
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.
Author(s)
Marco Scutari
See Also
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