Learn R Programming

stabs (version 0.6-4)

stabsel.stabsel: Change Parameters of Stability Selection

Description

Method to change the parameters cutoff, PFER and assumption of stability selection that can be altered without the need to re-run the subsampling process.

Usage

# S3 method for stabsel
stabsel(x, cutoff, PFER, assumption = x$assumption, ...)

Value

An object of class stabsel. For details see there.

Arguments

x

an object that results from a call to stabsel.

cutoff

cutoff between 0.5 and 1. Preferably a value between 0.6 and 0.9 should be used.

PFER

upper bound for the per-family error rate. This specifies the amount of falsely selected base-learners, which is tolerated. See details.

assumption

Defines the type of assumptions on the distributions of the selection probabilities and simultaneous selection probabilities. Only applicable for sampling.type = "SS". For sampling.type = "MB" we always use code"none".

...

additional arguments that are currently ignored.

Details

This function allows to alter the parameters cutoff, PFER and assumption of a fitted stability selection result. All other parameters are re-used from the original stability selection results. The missing paramter is computed and the selected variables are updated accordingly.

See Also

stabsel for the generic function, stabsel_parameters for the computation of error bounds, fitfun for available fitting functions and plot.stabsel for available plot functions

Examples

Run this code
  if (require("TH.data")) {
      ## make data set available
      data("bodyfat", package = "TH.data")
  } else {
      ## simulate some data if TH.data not available. 
      ## Note that results are non-sense with this data.
      bodyfat <- matrix(rnorm(720), nrow = 72, ncol = 10)
  }
  
  ## set seed
  set.seed(1234)

  ####################################################################
  ### using stability selection with Lasso methods:

  if (require("lars")) {
      (stab.lasso <- stabsel(x = bodyfat[, -2], y = bodyfat[,2],
                             fitfun = lars.lasso, cutoff = 0.75,
                             PFER = 1))

      par(mfrow = c(2, 1))
      plot(stab.lasso)

      ## now change the PFER and the assumption:
      (stab.lasso_cf0.93_rconc <- stabsel(stab.lasso, cutoff = 0.93,
                                          assumption = "r-concave"))
      plot(stab.lasso_cf0.93_rconc)
      ## the cutoff did change and hence the PFER and the selected
      ## variables
  }

Run the code above in your browser using DataLab