check_sample_fraction

Checks the input data of sample.fraction

internal

An implementation of the Ordered Forest estimator as developed
in Lechner & Okasa (2019) <arXiv:1907.02436>. The Ordered Forest flexibly
estimates the conditional probabilities of models with ordered categorical
outcomes (so-called ordered choice models). Additionally to common machine
learning algorithms the 'orf' package provides functions for estimating
marginal effects as well as statistical inference thereof and thus provides
similar output as in standard econometric models for ordered choice. The
core forest algorithm relies on the fast C++ forest implementation from
the 'ranger' package (Wright & Ziegler, 2017) <arXiv:1508.04409>.

Gabriel Okasa

Ordered Random Forests

check_sample_fraction function

<dl><dt>sample.fraction</dt>
<dd>scalar, fraction of data used for subsampling</dd>
<dt>replace</dt>
<dd>logical, if bootstrap or subsampling should be used</dd></dl>

Arguments

check sample.fraction — check_sample_fraction

<dl>

<dt>sample.fraction</dt>
<dd>scalar, fraction of data used for subsampling</dd>


<dt>replace</dt>
<dd>logical, if bootstrap or subsampling should be used</dd>

</dl>

check_sample_fraction: check sample.fraction

Description

Usage

Value

Arguments