PI: The plug-in bandwidth selection for weighted data
In Coxmos: Cox MultiBlock Survival
PI R Documentation
The plug-in bandwidth selection for weighted data
Description
This function computes the data-driven bandwidth for smoothing the ROC (or distribution) function using the PI method of Beyene and El Ghouch (2020). This is an extension of the classical (unweighted) direct plug-in bandwith selection method to the case of weighted data.
Usage
PI(X, wt, ktype = "normal")
Arguments
X
The numeric vector of random variable.
wt
The non-negative weight vector.
ktype
A character string giving the type kernel to be used: "normal", "epanechnikov", "biweight", or "triweight". By default, the "normal" kernel is used.
Details
See Beyene and El Ghouch (2020) for details.
Value
Returns the computed value for the bandwith parameter.
Author(s)
Kassu Mehari Beyene, Catholic University of Louvain. <kasu.beyene@uclouvain.be>
Anouar El Ghouch, Catholic University of Louvain. <anouar.elghouch@uclouvain.be>
References
Beyene, K. M. and El Ghouch A. (2020). Smoothed time-dependent ROC curves for right-censored survival data. submitted.
Coxmos documentation built on April 4, 2025, 12:20 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| PI | R Documentation |
The plug-in bandwidth selection for weighted data
Description
This function computes the data-driven bandwidth for smoothing the ROC (or distribution) function using the PI method of Beyene and El Ghouch (2020). This is an extension of the classical (unweighted) direct plug-in bandwith selection method to the case of weighted data.
Usage
PI(X, wt, ktype = "normal")
Arguments
X |
The numeric vector of random variable. |
wt |
The non-negative weight vector. |
ktype |
A character string giving the type kernel to be used: " |
Details
See Beyene and El Ghouch (2020) for details.
Value
Returns the computed value for the bandwith parameter.
Author(s)
Kassu Mehari Beyene, Catholic University of Louvain. <kasu.beyene@uclouvain.be>
Anouar El Ghouch, Catholic University of Louvain. <anouar.elghouch@uclouvain.be>
References
Beyene, K. M. and El Ghouch A. (2020). Smoothed time-dependent ROC curves for right-censored survival data. submitted.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.