conv_diff

<code>conv_diff</code> uses an object of class <code>"robust2sls"</code> to calculate the
L2 norm (sum of squared differences) between the most recent outlier-robust
iteration and the previous iteration estimates.

internal

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

conv_diff function

<dl><dt>current</dt>
<dd>A list object of class <code>"robust2sls"</code>.</dd>
<dt>counter</dt>
<dd>An integer denoting the number of the current iteration.</dd></dl>

Arguments

L2 norm between two most recent estimates — conv_diff

<dl>

<dt>current</dt>
<dd>A list object of class <code>"robust2sls"</code>.</dd>


<dt>counter</dt>
<dd>An integer denoting the number of the current iteration.</dd>

</dl>

conv_diff: L2 norm between two most recent estimates

Description

Usage

Value

Arguments