stabsel_stabsel: Change Parameters of Stability Selection
In stabs: Stability Selection with Error Control

Description Usage Arguments Details Value See Also Examples

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.

1 2	## S3 method for class 'stabsel' stabsel(x, cutoff, PFER, assumption = x$assumption, ...)

`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.

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.

An object of class stabsel. For details see there.

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

  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
  }