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SimultAnR (version 1.1)

CorrAn: Correspondence Analysis

Description

The CorrAn function computes the correspondence analysis of the selected data.

Usage

CorrAn(data, sr = NA, sc = NA, nd = 2, dp = 2, oar = 1, oac = 1, multiple = 0)

Arguments

data
Data set
sr
Indices of supplementary rows
sc
Indices of supplementary columns
nd
Number of dimensions in results
dp
Number of digits in results
oar
Output for active rows (1 = yes, 0 = no)
oac
Output for active columns (1 = yes, 0 = no)
multiple
Option for Multiple Simultaneous Analysis (1 = yes, 0 = no)

Value

totalin
Total inertia
eig
Eigenvalues
resin
Results of inertia
resi
Results of active rows
resj
Results of active columns
resisr
Results of supplementary rows
resjsc
Results of supplementary columns
X
Matrix X
totalk
Total of data table
I
Number of active rows
namei
Names of active rows
fi
Marginal of active rows
Fs
Projections of active rows
d2i
Chi-square distance of active rows to their average
J
Number of active columns
namej
Names of active columns
fj
Marginal of active columns
Gs
Projections of active columns
d2j
Chi-square distance of active columns to their average
Isr
Number of supplementary rows
nameisr
Names of supplementary rows
fisr
Marginal of supplementary rows
Fssr
Projections of supplementary rows
d2isr
Chi-square distance of supplementary rows to the average
Xsr
Matrix X for supplementary rows
Jsc
Number of supplementary columns
namejsc
Names of supplementary columns
fjsc
Marginal of supplementary columns
Gssc
Projections of supplementary columns
d2jsc
Chi-square distance of supplementary columns to the average

Details

The options sr and sc allow supplementary rows and columns to be specified.

References

Greenacre, M. (2007). Correspondence Analysis in Practice. 2nd edition. Chapman and Hall/CRC, London.

Lebart, L; Piron, M., Morineau, A. (2006). Statistique exploratoire multidimensionnelle: visualisations et inferences en fouille de donnees. 4th edition. Dunod, Paris.

See Also

plot.CorrAn, summary.CorrAn

Examples

Run this code

data(shoplifting)
dataCA <- shoplifting[1:13, 1:9]

### CA without supplementary elements
CorrAn(data=dataCA)

### CA with supplementary rows and without output for columns
CorrAn(data=dataCA, sr=13, oac=0)

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