(Internal) function that is used to run stability selection (i.e. to apply the fit-function to the subsamples. This function is not intended to be directly called.

```
run_stabsel(fitter, args.fitter, n, p, cutoff, q, PFER, folds, B, assumption,
sampling.type, papply, verbose, FWER, eval, names,
mc.preschedule = FALSE, ...)
```

fitter

a function to fit the model on subsamples. See argument
`fitfun`

of `stabsel`

for details.

args.fitter

a named list containing additional arguments that are
passed to `fitter`

. See argument `args.fitfun`

`stabsel`

for details.

n

the number of observations; needed for internal checks.

p

number of possible predictors (including intercept if applicable).

cutoff

cutoff between 0.5 and 1.

q

number of (unique) selected variables (or groups of variables depending on the model) that are selected on each subsample.

PFER

upper bound for the per-family error rate.

folds

a weight matrix that represents the subsamples.

B

number of subsampling replicates.

assumption

distributional assumption.

sampling.type

sampling type to be used.

papply

(parallel) apply function.

verbose

logical (default: `TRUE`

) that determines wether
`warnings`

should be issued.

FWER

deprecated. Only for compatibility with older versions, use PFER instead.

eval

logical. Determines whether stability selection is evaluated.

names

variable names that are used to label the results.

mc.preschedule

preschedule tasks?

…

additional arguments to be passed to next function.

An object of class `stabsel`

with the following elements:

selection probabilities.

elements with maximal selection probability greater
`cutoff`

.

maximum of selection probabilities.

cutoff used.

average number of selected variables used.

per-family error rate.

the number of effects subject to selection.

the sampling type used for stability selection.

the assumptions made on the selection probabilities.

This is an internal function that fits the actual models to the
subsamples, i.e., this is the work horse that runs stability
selection. Usually, one should use `stabsel`

, which
internally calls `run_stabsel`

.

`run_stabsel`

can be used by expert users to implement stability
selection methods for new model types.

For details (e.g. on arguments) see `stabsel`

.

B. Hofner, L. Boccuto and M. Goeker (2015), Controlling false
discoveries in high-dimensional situations: Boosting with stability
selection. *BMC Bioinformatics*, 16:144.
10.1186/s12859-015-0575-3.

For details see `stabsel`

.