Description Usage Arguments Details Value References See Also Examples
View source: R/OSCV_regfunctions.R
Computing ASE(h), the value of the ASE function for the local linear estimator in the regression context, for the given vector of h values.
1 | ASE_reg(h, desx, y, rx)
|
h |
numerical vector of bandwidth values, |
desx |
numerical vecror of design points, |
y |
numerical vecror of data points corresponding to the design points desx, |
rx |
numerical vecror of values of the regression function at desx. |
The average squared error (ASE) is used as a measure of performace of the local linear estimator based on the Gaussian kernel.
The vector of values of ASE(h) for the correponsing vector of h values.
Hart, J.D. and Yi, S. (1998) One-sided cross-validation. Journal of the American Statistical Association, 93(442), 620-631.
loclin
, h_ASE_reg
, CV_reg
, OSCV_reg
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ## Not run:
# Example (ASE function for a random sample of size n=100 generated from the function reg3 that
# has six cusps. The function originates from the article of Savchuk et al. (2013).
# The level of the added Gaussian noise is sigma=1/1000).
n=100
dx=(1:n-0.5)/n
regx=reg3(dx)
ydat=regx+rnorm(n,sd=1/1000)
harray=seq(0.003,0.05,len=300)
ASEarray=ASE_reg(harray,dx,ydat,regx)
hmin=round(h_ASE_reg(dx,ydat,regx),digits=4)
dev.new()
plot(harray,ASEarray,'l',lwd=3,xlab="h",ylab="ASE",main="ASE function for a random sample
from r3",cex.lab=1.7,cex.axis=1.7,cex.main=1.5)
legend(0.029,0.0000008,legend=c("n=100","sigma=1/1000"),cex=1.7,bty="n")
legend(0.005,0.000002,legend=paste("h_ASE=",hmin),cex=2,bty="n")
## End(Not run)
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