bwCV {BwQuant} | R Documentation |
Computing the cross-validation bandwidth proposed by Abberger (1998)
Description
Function to compute a bandwidth for local linear quantile regression following the cross-validation criteria presented by Abberger (1998).
Usage
bwCV(x, y, hseq, tau)
Arguments
x |
numeric vector of |
y |
numeric vector of |
hseq |
sequence of values where the cross-validation function will be evaluated. |
tau |
the quantile order where the regression function is to be estimated. It must be a number strictly between 0 and 1. |
Details
The cross-validation function is evaluated at each element of hseq
. Then, the cross-validation selector will be the element of hseq
that minimizes the cross-validation function.
Value
Returns a number with the chosen bandwidth.
Author(s)
Mercedes Conde-Amboage and Cesar Sanchez-Sellero.
References
Abberger, K. (1998). Cross-validation in nonparametric quantile regression. Allgemeines Statistisches Archiv, 82, 149-161.
Abberger, K. (2002). Variable data driven bandwidth choice in nonparametric quantile regression. Technical Report.
See Also
The obtained bandwidth can be used in the function llqr
to produce a local linear estimate of the tau
-quantile regression function.
Examples
set.seed(1234)
x=runif(100)
y=10*(x^4+x^2-x)+rexp(100)
hseq=seq(0.05,0.8,length=21)
tau=0.25
bwCV(x,y,hseq,tau)