R: Plot fitted Bayesian networks

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 = "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 (multinomial and ordinal) Bayesian networks.
    bn.fit.barchart(fitted, xlab = "Probabilities",
      ylab = "Levels", main = "Conditional Probabilities", ...)
    bn.fit.dotplot(fitted, xlab = "Probabilities",
      ylab = "Levels", main = "Conditional Probabilities", ...)

### 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.

### Author(s)

Marco Scutari

### See Also

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

[Package bnlearn version 4.3 Index]