kernelwts: Kernel Weighting function

In rdd: Regression Discontinuity Estimation

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).

Author(s)

Drew Dimmery <[e-mail]>

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")

Example output

Loading required package: sandwich
Loading required package: lmtest
Loading required package: zoo

Attaching package: 'zoo'

The following objects are masked from 'package:base':

    as.Date, as.Date.numeric

Loading required package: AER
Loading required package: car
Loading required package: carData
Loading required package: survival
Loading required package: Formula

rdd documentation built on May 2, 2019, 10:22 a.m.