Rpdata: Always plot residuals.

In alr4: Data to Accompany Applied Linear Regression 4th Edition

Description

This example with aritifical data is designed to demonstrate the importance of plotting residuals.

Usage

data(Rpdata)

Format

A data frame with 990 observations on the following 7 variables.

y

a numeric vector

x1

a numeric vector

x2

a numeric vector

x3

a numeric vector

x4

a numeric vector

x5

a numeric vector

x6

a numeric vector

Source

Data generated using programs from http://www4.stat.ncsu.edu/~stefanski/NSF_Supported/Hidden_Images/stat_res_plots.html

References

Stefanski, L. A. (2007). Residual (sur)Realism. The American Statistician, 61, 163-177. url=https://www.amstat.org/about/pdfs/NCSUStatsProfSurpriseHomework.pdf.

Examples

data(Rpdata)
## Not run: 
require(car)
residualPlot(lm(Rpdata))

## End(Not run)

Example output

Loading required package: car
Loading required package: effects
Loading required package: carData

Attaching package: 'carData'

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

    Guyer, UN, Vocab

lattice theme set by effectsTheme()
See ?effectsTheme for details.

alr4 documentation built on May 2, 2019, 6:40 p.m.