Initial_FUZZy_BIN

function that samples initial values for fuzzy LoTTA model with a known cutoff and binary outcomes

Implementation of the LoTTA (Local Trimmed Taylor Approximation) model
described in "Bayesian Regression Discontinuity Design with Unknown Cutoff"
by Kowalska, van de Wiel, van der Pas (2024) <doi:10.48550/arXiv.2406.11585>.

Julia Kowalska

LoTTA

Bayesian Inference in Regression Discontinuity Designs

Initial_FUZZy_BIN function

<dl><dt>x</dt>
<dd><ul>
<li>score data</li>
</ul></dd>
<dt>t</dt>
<dd><ul>
<li>treatment data</li>
</ul></dd>
<dt>y</dt>
<dd><ul>
<li>outcome data</li>
</ul></dd>
<dt>c</dt>
<dd><ul>
<li>cutoff location</li>
</ul></dd>
<dt>lb</dt>
<dd><ul>
<li>minimum window size</li>
</ul></dd>
<dt>ubr</dt>
<dd><ul>
<li>maximum value of the window's right boundary point</li>
</ul></dd>
<dt>ubl</dt>
<dd><ul>
<li>minimum value of the window's left boundary point</li>
</ul></dd>
<dt>s</dt>
<dd><ul>
<li>seed</li>
</ul></dd>
<dt>jlb</dt>
<dd><ul>
<li>minimum jump size</li>
</ul></dd></dl>

Arguments

function that samples initial values for fuzzy LoTTA model with a known cutoff and binary outcomes — Initial_FUZZy_BIN

<dl>

<dt>x</dt>
<dd><ul>
<li>score data</li>
</ul></dd>


<dt>t</dt>
<dd><ul>
<li>treatment data</li>
</ul></dd>


<dt>y</dt>
<dd><ul>
<li>outcome data</li>
</ul></dd>


<dt>c</dt>
<dd><ul>
<li>cutoff location</li>
</ul></dd>


<dt>lb</dt>
<dd><ul>
<li>minimum window size</li>
</ul></dd>


<dt>ubr</dt>
<dd><ul>
<li>maximum value of the window's right boundary point</li>
</ul></dd>


<dt>ubl</dt>
<dd><ul>
<li>minimum value of the window's left boundary point</li>
</ul></dd>


<dt>s</dt>
<dd><ul>
<li>seed</li>
</ul></dd>


<dt>jlb</dt>
<dd><ul>
<li>minimum jump size</li>
</ul></dd>

</dl>

Initial_FUZZy_BIN: function that samples initial values for fuzzy LoTTA model with a known cutoff and binary outcomes

Description

Usage

Value

Arguments