check_folds

(Internal) function that checks if folds result from subsampling with
 p = 0.5 and adds complementary pairs if needed.

helper

Resampling procedures to assess the stability of selected variables
with additional finite sample error control for high-dimensional variable
selection procedures such as Lasso or boosting. Both, standard stability
selection (Meinshausen & Buhlmann, 2010, <doi:10.1111/j.1467-9868.2010.00740.x>)
and complementary pairs stability selection with improved error bounds
(Shah & Samworth, 2013, <doi:10.1111/j.1467-9868.2011.01034.x>) are
implemented. The package can be combined with arbitrary user specified
variable selection approaches.

Benjamin Hofner

stabs

Stability Selection with Error Control

Torsten Hothorn

check_folds function

<dl> <dt>folds</dt>
<dd>a weight matrix that represents the subsamples.</dd> <dt>B</dt>
<dd>number of subsampling replicates.</dd> <dt>n</dt>
<dd>the number of observations; needed for internal checks.</dd> <dt>sampling.type</dt>
<dd>sampling type to be used.</dd></dl>

Arguments

Check if folds result from subsampling with p = 0.5 — check_folds

<dl>

 <dt>folds</dt>
<dd>a weight matrix that represents the subsamples.</dd>

 <dt>B</dt>
<dd>number of subsampling replicates.</dd>

 <dt>n</dt>
<dd>the number of observations; needed for internal checks.</dd>

 <dt>sampling.type</dt>
<dd>sampling type to be used.</dd>

</dl>

check_folds: Check if folds result from subsampling with p = 0.5

Description

Usage

Value

Arguments

Details

References

See Also