dudi.coa {ade4}R Documentation

Correspondence Analysis

Description

performs a correspondence analysis.

Usage

dudi.coa(df, scannf = TRUE, nf = 2)

Arguments

df a data frame containing positive or null values
scannf a logical value indicating whether the eigenvalues bar plot should be displayed
nf if scannf FALSE, an integer indicating the number of kept axes

Value

returns a list of class coa and dudi (see dudi) containing
N the sum of all the values of the initial table

Author(s)

Daniel Chessel
Anne B Dufour dufour@biomserv.univ-lyon1.fr

References

Benzécri, J.P. and Coll. (1973) L'analyse des données. II L'analyse des correspondances, Bordas, Paris. 1–620.

Greenacre, M. J. (1984) Theory and applications of correspondence analysis, Academic Press, London.

Examples

data(rpjdl)
chisq.test(rpjdl$fau)$statistic
rpjdl.coa <- dudi.coa(rpjdl$fau, scannf = FALSE, nf = 4)
sum(rpjdl.coa$eig)*rpjdl.coa$N # the same

par(mfrow = c(1,2))
s.label(rpjdl.coa$co, clab = 0.6, lab = rpjdl$frlab)
s.label(rpjdl.coa$li, clab = 0.6)
par(mfrow = c(1,1))

data(bordeaux)
db <- dudi.coa(bordeaux, scan = FALSE)
db
score(db)

Worked out examples


> library(ade4)
> ### Name: dudi.coa
> ### Title: Correspondence Analysis
> ### Aliases: dudi.coa
> ### Keywords: multivariate
> 
> ### ** Examples
> 
> data(rpjdl)
> chisq.test(rpjdl$fau)$statistic
X-squared 
 7323.597 
> rpjdl.coa <- dudi.coa(rpjdl$fau, scannf = FALSE, nf = 4)
> sum(rpjdl.coa$eig)*rpjdl.coa$N # the same
[1] 7323.597
> 
> par(mfrow = c(1,2))
> s.label(rpjdl.coa$co, clab = 0.6, lab = rpjdl$frlab)
> s.label(rpjdl.coa$li, clab = 0.6)
> par(mfrow = c(1,1))
> 
> data(bordeaux)
> db <- dudi.coa(bordeaux, scan = FALSE)
> db
Duality diagramm
class: coa dudi
$call: dudi.coa(df = bordeaux, scannf = FALSE)

$nf: 2 axis-components saved
$rank: 3
eigen values: 0.5906 0.1102 0.03109
  vector length mode    content       
1 $cw    4      numeric column weights
2 $lw    5      numeric row weights   
3 $eig   3      numeric eigen values  

  data.frame nrow ncol content             
1 $tab       5    4    modified array      
2 $li        5    2    row coordinates     
3 $l1        5    2    row normed scores   
4 $co        4    2    column coordinates  
5 $c1        4    2    column normed scores
other elements: N 
> score(db)
> 
> 
> 
> 

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