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.

This software package provides Cox survival analysis for high-dimensional and multiblock datasets.
It encompasses a suite of functions dedicated from the classical Cox regression to newest analysis,
including Cox proportional hazards model, Stepwise Cox regression, and Elastic-Net Cox regression,
Sparse Partial Least Squares Cox regression (sPLS-COX) incorporating three distinct strategies,
and two Multiblock-PLS Cox regression (MB-sPLS-COX) methods. This tool is designed to adeptly handle
high-dimensional data, and provides tools for cross-validation, plot generation, and additional resources
for interpreting results. While references are available within the corresponding functions,
key literature is mentioned below.
Terry M Therneau (2024) <https://CRAN.R-project.org/package=survival>,
Noah Simon et al. (2011) <doi:10.18637/jss.v039.i05>,
Philippe Bastien et al. (2005) <doi:10.1016/j.csda.2004.02.005>,
Philippe Bastien (2008) <doi:10.1016/j.chemolab.2007.09.009>,
Philippe Bastien et al. (2014) <doi:10.1093/bioinformatics/btu660>,
Kassu Mehari Beyene and Anouar El Ghouch (2020) <doi:10.1002/sim.8671>,
Florian Rohart et al. (2017) <doi:10.1371/journal.pcbi.1005752>.

Pedro Salguero Garcia

Coxmos

Cox MultiBlock Survival

Pedro Salguero García

Sonia Tarazona Campos

Ana Conesa Cegarra

Kassu Mehari Beyene

Luis Meira Machado

Marta Sestelo

Artur Araújo

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