Gentleman and Geyer's Data

Description

Gentleman and Geyer's Data.

Usage

data(ICGG)

Format

A data frame with 6 observations on the following 2 variables.

left

the left interval endpoint

right

the right interval endpoint

Source

Gentleman, R. and Geyer, C. (1994) Maximum Likelihood for Interval Censored Data: Consistency and Computation. Biometrika.

Examples

 library(KernSmooth)
 tmp <- apply(ICGG, 1, mean)  # tmp now contains the interval midpoints
 h <- dpik(tmp)               # direct-plug-in bandwidth selected for
                              # interval midpoints
 par(mfrow=c(1,2))
 estimate <- ickde(ICGG, h=h, m=200)
 plot(estimate, type="l", main="One fixed point")
 estimate <- ickde(ICGG, f=c(rep(1,60),rep(0,90),rep(1,60)), h=.1)
 plot(estimate, type="l", main="Another fixed point")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(ICE)
Loading required package: KernSmooth
KernSmooth 2.23 loaded
Copyright M. P. Wand 1997-2009
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ICE/ICGG.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ICGG
> ### Title: Gentleman and Geyer's Data
> ### Aliases: ICGG
> ### Keywords: datasets
> 
> ### ** Examples
> 
>  library(KernSmooth)
>  tmp <- apply(ICGG, 1, mean)  # tmp now contains the interval midpoints
>  h <- dpik(tmp)               # direct-plug-in bandwidth selected for
>                               # interval midpoints
>  par(mfrow=c(1,2))
>  estimate <- ickde(ICGG, h=h, m=200)
>  plot(estimate, type="l", main="One fixed point")
>  estimate <- ickde(ICGG, f=c(rep(1,60),rep(0,90),rep(1,60)), h=.1)
>  plot(estimate, type="l", main="Another fixed point")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>