multi_cutoff_to_fodr_vec

<code>multi_cutoff_to_fodr_vec()</code> takes a list of <code>"robust2sls"</code> objects
and returns a vector of the centered FODR (sample - expected) for different
values of the cut-off c (equivalently gamma): n(_c - _c) sqrt(n)(gamma_hat - gamma)

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

multi_cutoff_to_fodr_vec function

<dl><dt>robust2sls_object</dt>
<dd>A list of <code>"robust2sls"</code> objects.</dd>
<dt>iteration</dt>
<dd>An integer &gt;= 0 or the character "convergence" that
determines which iteration is used for the test.</dd></dl>

Arguments

<code>multi_cutoff_to_fodr_vec()</code> takes a list of <code>"robust2sls"</code> objects
and returns a vector of the centered FODR (sample - expected) for different
values of the cut-off c (equivalently gamma):

 n(_c - _c) sqrt(n)(gamma_hat - gamma)

Creates a vector of the centered FODR across different cut-offs — multi_cutoff_to_fodr_vec

<dl>

<dt>robust2sls_object</dt>
<dd>A list of <code>"robust2sls"</code> objects.</dd>


<dt>iteration</dt>
<dd>An integer &gt;= 0 or the character "convergence" that
determines which iteration is used for the test.</dd>

</dl>

multi_cutoff_to_fodr_vec: Creates a vector of the centered FODR across different cut-offs

Description

Usage

Value

Arguments

Details