iclocpoly: Interval-Censored Local Polynomial Regression Estimation

In ICE: Iterated Conditional Expectation

Description

Local polynomial regression estimation for interval-censored data.

Usage

iclocpoly(x, y=NULL, y.IC, degree=0, h, niter=10, kernel="normal", gridsize=401)

Arguments

x	uncensored explanatory variable vector
y	uncensored portion of response vector (optional)
y.IC	two-column matrix of left and right interval endpoints for censored responses
degree	degree of local polynomial
h	bandwidth
niter	number of iterations
kernel	smoothing kernel to be used; default is "normal"; other choices as in the function locpoly
gridsize	number of gridpoints; again as in locpoly

Value

A list consisting of the explanatory variable x and the imputed responses y as well as the estimate of sigma. Usually, one would apply locpoly with a similar bandwidth to obtain the final fitted model.

Examples

library(KernSmooth)
data(motor.IC)
estimate <- iclocpoly(x=motor.IC$V1, y.IC = cbind(motor.IC$y.L, 
motor.IC$y.R), degree=0, h=1)
plot(motor.IC$V1, motor.IC$V2)
lines(locpoly(estimate$x, estimate$y, bandwidth=1, degree=0),col=4)

ICE documentation built on May 29, 2017, 4:15 p.m.

Interval-Censored Local Linear Density Estimation

ICE index

Innermost Intervals for Interval-Censored Data