CPScluster: Clusterings for the US Current Population Survey.

Description Usage Format Examples

Description

Different hierarchical clusterings and k-means clusterings as well as a model-based clustering have been applied to several financial variables for a random sample of ten thousand observations.

Usage

1

Format

A data frame with 10000 observations on the following 39 variables.

Age

a numeric vector

Sex

a factor with levels female male

Race

a factor with levels Black White

Ethnic

a factor

Marital.Status

a factor

Kind.of.Family

a factor

Classical

a factor with levels All other Classical Husband-Wife family

Family.Type

a factor

Number.of.Persons.in.Family

a numeric vector

Number.of.Kids

a numeric vector

Education.of.Head

a factor

Labor.Status

a factor

Class.of.Worker

a factor

Working.Hours

a numeric vector

Income.of.Head

a numeric vector

Family.Income

a numeric vector

Taxable.Income

a numeric vector

Federal.tax

a numeric vector

Family.sequence.number

a numeric vector

State

a factor

Division

a factor

Region

a factor with levels Midwest North East South West

hc4

a numeric vector

hc6

a numeric vector

hc8

a numeric vector

hc12

a numeric vector

hcs4

a numeric vector

hcs6

a numeric vector

hcs8

a numeric vector

hcs12

a numeric vector

hcw4

a numeric vector

hcw6

a numeric vector

hcw8

a numeric vector

hcw12

a numeric vector

km4

a numeric vector

km6

a numeric vector

km8

a numeric vector

km12

a numeric vector

mc12

a numeric vector

Examples

1
2
data(CPScluster)
## maybe str(CPScluster) ; plot(CPScluster) ...

extracat documentation built on July 17, 2018, 5:05 p.m.