relsharp_bigh {sharpPen}

Ridge/Enet/LASSO Sharpening via the local polynomial regression with large bandwidth.

Description

This is a function to shrink responses towards their estimations of local polynomial regression with large bandwidth as a form of data sharpening to remove roughness, prior to use in local polynomial regression.

Usage

 relsharp_bigh(x, y, alpha, bigh) 

Arguments

x

numeric vector of equally spaced x data. Missing values are not accepted.

y

vector of y data. Missing values are not accepted.

alpha

the elasticnet mixing parameter vector, with alpha in [0,1].

bigh

the kernel bandwidth smoothing parameter.

Details

Note that the predictor values are assumed to be equally spaced.

Value

numeric matrix of sharpened responses, with each column corresponding to different values of alpha

Author(s)

D.Wang

Examples

x<-seq(0,10,length=100)
g <- function(x) sin(x)
y<-g(x)+rnorm(100)
ys<-relsharp_bigh(x, y,alpha=c(0.2,0.8), dpill(x,y)*4)
y.lp2<-locpoly(x,ys[,1],bandwidth=dpill(x,y),degree=1,gridsize=100)
y.lp8<-locpoly(x,ys[,2],bandwidth=dpill(x,y),degree=1,gridsize=100)
y.lp<-locpoly(x,y,bandwidth=dpill(x,y),degree=1,gridsize=100)
curve(g,x,xlim=c(0,10))
lines(y.lp2,col=2)
lines(y.lp8,col=3)
lines(y.lp,col=5)
norm(as.matrix(g(x) - y.lp2$y),type="2")
norm(as.matrix(g(x) - y.lp8$y),type="2")
norm(as.matrix(g(x) - y.lp$y),type="2")