summary.PimpTest

print.summary.PimpTest

an object of class <code>PimpTest</code>, a result of a call to <code><a rd-options="vita" href="/link/PimpTest?package=vita&version=1.0.0&to=vita" data-mini-rdoc="vita::PimpTest">PimpTest</a></code>.

object

 print only p-values less than pless.  Default is <code>pless=0.05</code>.

pless

an object of class <code>summary.PimpTest</code>, a result of a call to <code>summary.PimpTest</code>.

further arguments passed to or from other methods.


<code>summary </code>method for class <code>"PimpTest"</code>.


Implements the novel testing approach by Janitza et al.(2015)
<http://nbn-resolving.de/urn/resolver.pl?urn=nbn:de:bvb:19-epub-25587-4>
for the permutation variable importance measure in a random forest and the
PIMP-algorithm by Altmann et al.(2010) <doi:10.1093/bioinformatics/btq134>.
Janitza et al.(2015) <http://nbn-resolving.de/urn/resolver.pl?urn=nbn:de:bvb:19-epub-25587-4>
do not use the "standard" permutation variable
importance but the cross-validated permutation variable
importance for the novel test approach. The cross-validated
permutation variable importance is not based on the out-of-bag
observations but uses a similar strategy which is inspired by
the cross-validation procedure. The novel test approach can be
applied for classification trees as well as for regression
trees. However, the use of the novel testing approach has not
been tested for regression trees so far, so this routine is
meant for the expert user only and its current state is rather
experimental.

summary.PimpTest: Summarizing PIMP-algorithm outcomes

Description

Usage

Arguments

Value

Details

See Also