This function computes the data-driven bandwidth for smoothing the ROC (or distribution) function using the NR method of Beyene and El Ghouch (2020). This is an extension of the classical (unweighted) normal reference bandwith selection method to the case of weighted data.

internal

This contains functions that can be used to estimate a smoothed and
a non-smoothed (empirical) time-dependent receiver operating characteristic
curve and the corresponding area under the receiver operating characteristic
curve for correlated right-censored time-to-event data. See
Beyene and Chen (2024) <doi:10.1177/09622802231220496>.

Kassu Mehari Beyene

frailtyROC

Time-Dependent ROC Curve Estimation for Correlated
Right-Censored Survival Data

Ding-Geng Chen

NR function

<dl><dt>X</dt>
<dd>The numeric data vector.</dd>
<dt>wt</dt>
<dd>The non-negative weight vector.</dd>
<dt>ktype</dt>
<dd>A character string giving the type kernel to be used: "<code>normal</code>", "<code>epanechnikov</code>", "<code>biweight</code>", or "<code>triweight</code>". By default, the "<code>normal</code>" kernel is used.</dd></dl>

Arguments

Kassu Mehari Beyene, Catholic University of Louvain. <code>&lt;kasu.beyene@uclouvain.be&gt;</code>
Anouar El Ghouch, Catholic University of Louvain. <code>&lt;anouar.elghouch@uclouvain.be&gt;</code>

Author

The normal reference bandwidth selection for weighted data — NR

<dl>

<dt>X</dt>
<dd>The numeric data vector.</dd>


<dt>wt</dt>
<dd>The non-negative weight vector.</dd>


<dt>ktype</dt>
<dd>A character string giving the type kernel to be used: "<code>normal</code>", "<code>epanechnikov</code>", "<code>biweight</code>", or "<code>triweight</code>". By default, the "<code>normal</code>" kernel is used.</dd>

</dl>

NR: The normal reference bandwidth selection for weighted data

Description

Usage

Value

Arguments

Author

Details

References