plot.ensemble {randomSurvivalForest}R Documentation

Plot of Ensemble Estimates

Description

Plot ensemble survival curves and ensemble estimates of mortality.

Usage

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

Arguments

x An object of class randomSurvivalForest, as that created by the function rsf.
main Plot title.
... Further arguments passed to or from other methods.

Details

Four plots are produced. Going from top to bottom, left to right: (1) This shows the ensemble survival function for each individual in the data. Thick red line is overall ensemble survival, thick green line is Nelson-Aalen estimator. (2) This is a comparison of the population ensemble survival function to the Nelson-Aalen estimator. (3) The Brier score, a value between 0 and 1 (where 0=perfect, 1=poor, and 0.25=guessing; see reference below) is plotted at each of the unique event times with plot stratified by ensemble mortality value. Stratification is into 4 groups corresponding to the 0-25, 25-50, 50-75 and 75-100 percentile values of mortality. Green line is non-stratified score. (4) Plot of estimated mortality versus observed time. Points in blue correspond to events, black points are censored observations.

Author(s)

Hemant Ishwaran hemant.ishwaran@gmail.com and Udaya B. Kogalur ubk2101@columbia.edu

References

H. Ishwaran and Udaya B. Kogalur (2006). Random Survival Forests. Cleveland Clinic Technical Report.

E. Graf, C. Schmoor, W. Sauerbrei and M. Schumacher M (1999). Assessment and comparison of prognostic classification schemes for survival data, Statistics in Medicine, 18:2529-2545.

See Also

rsf, print.rsf, plot.variable, plot.error, plot.proximity.

Examples

  data(veteran, package = "randomSurvivalForest") 
  v.out <- rsf(Survrsf(time, status)~., veteran, ntree = 1000)
  plot.ensemble(v.out)

[Package randomSurvivalForest version 1.0.0 Index]