rfPermute: plotNull – R documentation

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plotNull

Plot Random Forest Importance Null Distributions

Description

Plot the Random Forest null distributions importance metrics, observed values, and p-values for each predictor variable from the object produced by a call to rfPermute.

Usage

plotNull(
  x,
  preds = NULL,
  imp.type = NULL,
  scale = TRUE,
  plot.type = c("density", "hist"),
  plot = TRUE
)

Arguments

`x`	An object produced by a call to `rfPermute`.
`preds`	a character vector of predictors to plot. If `NULL`, then all predictors are plotted.
`imp.type`	Either a numeric or character vector giving the importance metric(s) to plot.
`scale`	Plot importance measures scaled (divided by) standard errors?
`plot.type`	type of plot to produce: `"density"` for smoothed density plot, or `"hist"` for histogram.
`plot`	display the plot?

Details

The function will generate an plot for each predictor, with facetted importance metrics. The vertical red line shows the observed importance score and the p-value is given in the facet label.

Value

A named list of the ggplot figures produced is invisbly returned.

Author(s)

Eric Archer eric.archer@noaa.gov

Examples

# A regression model using the ozone example
data(airquality)
ozone.rfP <- rfPermute(
  Ozone ~ ., data = airquality, ntree = 100, 
  na.action = na.omit, nrep = 50, num.cores = 1
)
  
# Plot the null distributions and observed values.
plotNull(ozone.rfP)

rfPermute

Estimate Permutation p-Values for Random Forest Importance Metrics

v2.1.81

GPL (>= 2)

Authors

Eric Archer [aut, cre]

Initial release