h_opt_density

<code>h_opt_density</code> calculates theoretical optimal bandwidth.

internal

Density discontinuity testing (a.k.a. manipulation testing) is commonly employed in regression discontinuity designs and other program evaluation settings to detect perfect self-selection (manipulation) around a cutoff where treatment/policy assignment changes. This package implements manipulation testing procedures using the local polynomial density estimators: rddensity() to construct test statistics and p-values given a prespecified cutoff, rdbwdensity() to perform data-driven bandwidth selection, and rdplotdensity() to construct density plots.

Xinwei Ma

rddensity

Manipulation Testing Based on Density Discontinuity

Michael Jansson

h_opt_density function

<dl><dt>x</dt>
<dd>Numeric vector or data matrix, the running variable.</dd>
<dt>p</dt>
<dd>Integer, polynomial order.</dd>
<dt>N</dt>
<dd>Integer, sample size.</dd>
<dt>dgp_F1, dgp_Fp1</dt>
<dd>Numeric, theoretical d.g.p.</dd>
<dt>f_low, f_up</dt>
<dd>Numeric, lower and upper boundaries.</dd>
<dt>kernel</dt>
<dd>String, the kernel function, can be <code>triangular</code> (default),
<code>uniform</code> or <code>epanechnikov</code>.</dd></dl>

Arguments

Internal function, calculates theoretical optimal bandwidth. — h_opt_density

<dl>

<dt>x</dt>
<dd>Numeric vector or data matrix, the running variable.</dd>


<dt>p</dt>
<dd>Integer, polynomial order.</dd>


<dt>N</dt>
<dd>Integer, sample size.</dd>


<dt>dgp_F1, dgp_Fp1</dt>
<dd>Numeric, theoretical d.g.p.</dd>


<dt>f_low, f_up</dt>
<dd>Numeric, lower and upper boundaries.</dd>


<dt>kernel</dt>
<dd>String, the kernel function, can be <code>triangular</code> (default),
<code>uniform</code> or <code>epanechnikov</code>.</dd>

</dl>

h_opt_density: Internal function, calculates theoretical optimal bandwidth.

Description

Usage

Value

Arguments

Details