hw: Articial data with classical outliers.

In gmonette/spida2: Collection of tools developed for the Summer Programme in Data Analysis 2000-2012

Articial data with classical outliers.

Description

Articial data on health as predicted by height and weight with outliers to show the effect of different types of outliers.

Usage

data(hw)

data(hwoutliers)

Format

A data frame with 4 datasets, indexed by Type, each with 15 'good' observations. The last 3 datasets eadh contain, in addition to the 'good' data, an outlier.

Weight

a measure of body weight

Height

a measure of height

Health

an index of health: higher is better

Type

numerical type, 0, 1, 2 or 3

Outlier

a factor with levels none Type 1 Type 2 Type 3

Details

hw has four datasets identified by Outlier indicating the 'type' of outlier depicted in each dataset: none, Type 1: large residual for y with typical value of x, Type 2: small residual for y with atypical value of x, and Type 3: atypical x and poorly fitting y. hwoutliers contains the rows of 'acceptable' data and one row for each of the three types of outlier. This format lends itself better to 3-D plots. Note that this nomenclature for outlier is not widely adopted!

Examples

data(hw)
## maybe str(hw) ; plot(hw) ...

gmonette/spida2 documentation built on Aug. 20, 2023, 7:21 p.m.