CONT_outcome_function_sample

Function that evaluates the continuous outcome function in a domain x, given the coefficients

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

CONT_outcome_function_sample function

<dl><dt>coef_s</dt>
<dd><ul>
<li>list with the function coefficients</li>
</ul></dd>
<dt>x</dt>
<dd><ul>
<li>points at which the function is evaluated</li>
</ul></dd>
<dt>d_x</dt>
<dd><ul>
<li>shifting parameter that was used to normalize x</li>
</ul></dd>
<dt>s_x</dt>
<dd><ul>
<li>scaling parameter that was used to normalize x</li>
</ul></dd>
<dt>mu_y</dt>
<dd><ul>
<li>shifting parameter that was used to normalize y</li>
</ul></dd>
<dt>sd_y</dt>
<dd><ul>
<li>scaling parameter that was used to normalize y</li>
</ul></dd></dl>

Arguments

Function that evaluates the continuous outcome function in a domain x, given the coefficients — CONT_outcome_function_sample

<dl>

<dt>coef_s</dt>
<dd><ul>
<li>list with the function coefficients</li>
</ul></dd>


<dt>x</dt>
<dd><ul>
<li>points at which the function is evaluated</li>
</ul></dd>


<dt>d_x</dt>
<dd><ul>
<li>shifting parameter that was used to normalize x</li>
</ul></dd>


<dt>s_x</dt>
<dd><ul>
<li>scaling parameter that was used to normalize x</li>
</ul></dd>


<dt>mu_y</dt>
<dd><ul>
<li>shifting parameter that was used to normalize y</li>
</ul></dd>


<dt>sd_y</dt>
<dd><ul>
<li>scaling parameter that was used to normalize y</li>
</ul></dd>

</dl>

CONT_outcome_function_sample: Function that evaluates the continuous outcome function in a domain x, given the coefficients

Description

Usage

Value

Arguments