outliers

<code>outliers</code> calculates the number of outliers 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 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

Number of outliers — outliers

<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: Number of outliers

Description

Usage

Value

Arguments