auditor (version 0.3.0)

plotPrediction: Predicted response vs Observed or Variable Values

Description

Plot of predicted response vs observed or variable Values.

Usage

plotPrediction(object, ..., variable = NULL, smooth = FALSE,
  abline = TRUE, split = "none")

Arguments

object

An object of class modelAudit or modelResiduals.

...

Other modelAudit or modelResiduals objects to be plotted together.

variable

Only for modelAudit objects. Name of model variable to order residuals. If value is NULL data order is taken. If value is "Observed response" the data is ordered by a vector of actual response (y parameter passed to the audit function).

smooth

Logical, indicates whenever smooth line should be added.

abline

Logical, indicates whenever function y=x should be added.

split

Character. If "model" plot will be splitted by model.

See Also

plot.modelAudit

Examples

# NOT RUN {
library(car)
lm_model <- lm(prestige~education + women + income, data = Prestige)
lm_au <- audit(lm_model, data = Prestige, y = Prestige$prestige)
plotPrediction(lm_au)

library(randomForest)
rf_model <- randomForest(prestige~education + women + income, data = Prestige)
rf_au <- audit(rf_model, data = Prestige, y = Prestige$prestige)
plotPrediction(lm_au, rf_au)

# }