gen.data: Generate simulated data

In rpst: Recursive Partitioning Survival Trees

Description

Generate survival data for simulations.

Usage

  gen.data(n=100, p=10, c = 4, beta = NULL)

Arguments

n	The number of observations.
p	The number of predictors of interest.
c	The censoring paramter to control the censoring rate. Default is 4.
beta	The coefficient values in the underlying regression model.

Value

A list with the following components: data, beta.

data	The simulated dataset.
beta	The coefficients.

Author(s)

Yewei Li

References

Zhang, H., Legro, R. S., Zhang, J., Zhang, L., Chen, X., Huang, H., ... & Eisenberg, E. (2010). Decision trees for identifying predictors of treatment effectiveness in clinical trials and its application to ovulation in a study of women with polycystic ovary syndrome.. Human Reproduction, 25(10), 2612-2621.

See Also

rpst, predict.rpst, plot.rpst.

Examples

#require(survival)
data <- gen.data(n = 20, p = 5, c = 2)
tree <- rpst(data$data, minsize = 2)
print.rpst(tree)

rpst documentation built on May 2, 2019, 3:33 p.m.