Change Parameters of Stability Selection

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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

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

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.

Value

An object of class stabsel. For details see there.

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

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  ## make data set available
  data("bodyfat", package = "TH.data")
  ## 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
  }