# varimp.pmforest

From model4you v0.9-5
by Heidi Seibold

##### Variable Importance for pmforest

See `varimp.cforest`

.

##### Usage

```
# S3 method for pmforest
varimp(object, nperm = 1L, OOB = TRUE,
risk = function(x, ...) -objfun(x, sum = TRUE, ...),
conditional = FALSE, threshold = 0.2, ...)
```

##### Arguments

- object
DESCRIPTION.

- nperm
the number of permutations performed.

- OOB
a logical determining whether the importance is computed from the out-of-bag sample or the learning sample (not suggested).

- risk
the risk to be evaluated. By default the objective function (e.g. log-Likelihood) is used.

- conditional
a logical determining whether unconditional or conditional computation of the importance is performed.

- threshold
the value of the test statistic or 1 - p-value of the association between the variable of interest and a covariate that must be exceeded inorder to include the covariate in the conditioning scheme for the variable of interest (only relevant if conditional = TRUE).

- ...
passed on to

`objfun`

.

##### Value

A vector of 'mean decrease in accuracy' importance scores.

*Documentation reproduced from package model4you, version 0.9-5, License: GPL-2 | GPL-3*

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