rlcv: Robust likelihood cross validation bandwidth for univariate...

In rlcv: Robust Likelihood Cross Validation Bandwidth Selection

Robust likelihood cross validation bandwidth for univariate densities

Description

Robust likelihood cross validation bandwidth for univariate densities

Usage

rlcv(x.obs, x.new = NULL)

Arguments

x.obs	Training (observed) data
x.new	Evaluation data; default to x.obs

Value

fhat: density evaluated at x.new; h: bandwidth

Author(s)

Ximing Wu [e-mail]

References

Wu, Ximing (2019), "Robust Likelihood Cross Validation for Kernel Density Estimation," Journal of Business and Economic Statistics, 37(4): 761-770.

Examples

x=rt(200,df=5)
x.new=seq(-5,5,length=100)
fit=rlcv(x.obs=x,x.new=x.new)
# Mean squared errors
f0=dt(x.new,df=5)
mean((f0-fit$fhat)^2)

matplot(x.new,cbind(f0,fit$fhat),type='l')

rlcv documentation built on March 18, 2022, 6:35 p.m.