rdd (version 0.57)

kernelwts: Kernel Weighting function

Description

This function will calculate the appropriate kernel weights for a vector. This is useful when, for instance, one wishes to perform local regression.

Usage

kernelwts(X, center, bw, kernel = "triangular")

Arguments

X

input x values. This variable represents the axis along which kernel weighting should be performed.

center

the point from which distances should be calculated.

bw

the bandwidth.

kernel

a string indicating the kernel to use. Options are "triangular" (the default), "epanechnikov", "quartic", "triweight", "tricube", "gaussian", and "cosine".

Value

A vector of weights with length equal to that of the X input (one weight per element of X).

Examples

require(graphics)

X<-seq(-1,1,.01)
triang.wts<-kernelwts(X,0,1,kernel="triangular")
plot(X,triang.wts,type="l")

cos.wts<-kernelwts(X,0,1,kernel="cosine")
plot(X,cos.wts,type="l")