rf.partial.ci: Random Forests regression partial dependency plot with...
In rfUtilities: Random Forests Model Selection and Performance Evaluation

Description Usage Arguments Value Note Author(s) Examples

Plots the partial dependency, and associated confidence intervals, of a random forests regression model

1 2	rf.partial.ci(m, x, yname, xname, lci = 0.25, uci = 0.75, delta = FALSE)

`m`	randomForest regression object
`x`	data.frame or matrix of independent variables used to build model
`yname`	Name of the dependent variable
`xname`	Name of the independent variable for calculating partial dependence
`lci`	Percentile of predictions to plot as the lower bound.
`uci`	Percentile of predictions to plot as the upper bound.
`delta`	Plot change in prediction between the independent variable and simulated values (Default = NULL)

recordedplot object to recall plot

depends: randomForest

Jeffrey S. Evans <jeffrey_evans@tnc.org>

 library(randomForest)
 data(airquality)
 airquality <- na.omit(airquality)
 rf.ozone <- randomForest(y=airquality[,"Ozone"], airquality[,2:ncol(airquality)])

 par(mfrow=c(2,2))
   for(i in c("Solar.R", "Wind", "Temp", "Day")){
     rf.partial.ci(m=rf.ozone, x=airquality, yname="Ozone", xname=i, delta=TRUE) 
   }