outliers_prop

<code>outliers_prop</code> calculates the proportion of outliers relative to all
non-missing observations in the full sample from a <code>"robust2sls"</code> object
for a given iteration.

An implementation of easy tools for outlier robust inference in
two-stage least squares (2SLS) models. The user specifies a reference
distribution against which observations are classified as outliers or not.
After removing the outliers, adjusted standard errors are automatically
provided. Furthermore, several statistical tests for the false outlier
detection rate can be calculated. The outlier removing algorithm can be
iterated a fixed number of times or until the procedure converges. The
algorithms and robust inference are described in more detail in Jiao (2019)
<https://drive.google.com/file/d/1qPxDJnLlzLqdk94X9wwVASptf1MPpI2w/view>.

Jonas Kurle

robust2sls

Outlier Robust Two-Stage Least Squares Inference and Testing

outliers_prop function

<dl><dt>robust2sls_object</dt>
<dd>An object of class <code>"robust2sls"</code>.</dd>
<dt>iteration</dt>
<dd>An integer &gt;= 0 representing the iteration for which the
outliers are calculated.</dd></dl>

Arguments

Proportion of outliers — outliers_prop

<dl>

<dt>robust2sls_object</dt>
<dd>An object of class <code>"robust2sls"</code>.</dd>


<dt>iteration</dt>
<dd>An integer &gt;= 0 representing the iteration for which the
outliers are calculated.</dd>

</dl>

outliers_prop: Proportion of outliers

Description

Usage

Value

Arguments