plot.ooberror: Plot of OOB Error Rate

In tanujitdey/modelSampler: A unique tool for variable selection and model exploration in linear regression model

Description

Plot out-of-bag (OOB) error rate from the conditional ensemble estimation.

Usage

    plot.ooberror(x, main = deparse(substitute(x)), ...)

Arguments

x	An object of class boot.modelSampler, created by the function boot.modelSampler. See below.
main	Title of the plot.
...	Further arguments passed to or from other methods.

Details

An out-of-bag estimated prediction error (PE) plot will give a visualization of the "best" dimension of model. Red points are model size specific estimated PE. Dotted black lines are PE +/- s.e(PE). Smoothed black line represents loess estimated line of PE.

Author(s)

Tanujit Dey [e-mail]

References

Dey, T. (2013). modelSampler: An R Tool for Variable Selection and Model Exploration in Linear Regression. Journal of Data Science, 11(2), 371-387.

See Also

boot.modelSampler, modelSampler, print.boot.modelSampler, print.modelSampler, plot.modelSampler, plot.icicle, plot.var.stability, plot.FPE.

Examples

  data(Pollute, package = "modelSampler") 
  ms.boot <- boot.modelSampler(MortRate~., Pollute, n.iter1=2500, 
  n.iter2=2500, B=20, verbose = TRUE)
  plot.ooberror(ms.boot, main="Pollute Data")

tanujitdey/modelSampler documentation built on May 5, 2019, 11:01 p.m.