class_honest_split

Randomly spits the sample into a training sample and an honest sample.

internal

Nonparametric estimator of the ordered choice model using random forests. The estimator modifies a
standard random forest splitting criterion to build a collection of forests, each estimating the conditional
probability of a single class. The package also implements a nonparametric estimator of the covariates’ marginal effects.

Riccardo Di Francesco

morf

Modified Ordered Random Forest

class_honest_split function

<dl><dt>data</dt>
<dd><code>data.frame</code> or <code>matrix</code> to be split. The outcome must be located in the first column.</dd>
<dt>honesty.fraction</dt>
<dd>Fraction of honest sample.</dd></dl>

Arguments

Honest Sample Split — class_honest_split

<dl>

<dt>data</dt>
<dd><code>data.frame</code> or <code>matrix</code> to be split. The outcome must be located in the first column.</dd>


<dt>honesty.fraction</dt>
<dd>Fraction of honest sample.</dd>

</dl>

class_honest_split: Honest Sample Split

Description

Usage

Value

Arguments

Details