# bn.fit.plots: Plot fitted Bayesian networks In bnlearn: Bayesian Network Structure Learning, Parameter Learning and Inference

 bn.fit plots 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 `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.

### 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.

Marco Scutari

### See Also

`bn.fit`, `bn.fit class`.

bnlearn documentation built on May 29, 2024, 5:07 a.m.