# witwit.coa: Internal Correspondence Analysis In ade4: Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

 witwit.coa R Documentation

## Internal Correspondence Analysis

### Description

`witwit.coa` performs an Internal Correspondence Analysis. `witwitsepan` gives the computation and the barplot of the eigenvalues for each separated analysis in an Internal Correspondence Analysis.

### Usage

```witwit.coa(dudi, row.blocks, col.blocks, scannf = TRUE, nf = 2)
## S3 method for class 'witwit'
summary(object, ...)
witwitsepan(ww, mfrow = NULL, csub = 2, plot = TRUE)
```

### Arguments

 `dudi` an object of class `coa` `row.blocks` a numeric vector indicating the row numbers for each block of rows `col.blocks` a numeric vector indicating the column numbers for each block of columns `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

 `object` an object of class `witwit` `...` further arguments passed to or from other methods

 `ww` an object of class `witwit` `mfrow` a vector of the form "c(nr,nc)", otherwise computed by a special own function 'n2mfrow' `csub` a character size for the sub-titles, used with `par("cex")*csub` `plot` if FALSE, numeric results are returned

### Value

returns a list of class `witwit`, `coa` and `dudi` (see as.dudi) containing

 `rbvar` a data frame with the within variances of the rows of the factorial coordinates `lbw` a data frame with the marginal weighting of the row classes `cvar` a data frame with the within variances of the columns of the factorial coordinates `cbw` a data frame with the marginal weighting of the column classes

### Author(s)

Daniel Chessel Anne-Béatrice Dufour anne-beatrice.dufour@univ-lyon1.fr Correction by Campo Elías PARDO cepardot@cable.net.co

### References

Cazes, P., Chessel, D. and Dolédec, S. (1988) L'analyse des correspondances internes d'un tableau partitionné : son usage en hydrobiologie. Revue de Statistique Appliquée, 36, 39–54.

### Examples

```data(ardeche)
coa1 <- dudi.coa(ardeche\$tab, scann = FALSE, nf = 4)
ww <- witwit.coa(coa1, ardeche\$row.blocks, ardeche\$col.blocks, scann = FALSE)
ww
summary(ww)

g1 <- s.class(ww\$co, ardeche\$sta.fac, plab.cex = 1.5, ellipseSi = 0, paxes.draw = FALSE,
plot = FALSE)
g2 <- s.label(ww\$co, plab.cex = 0.75, plot = FALSE)
G <- superpose(g1, g2, plot = TRUE)

} else {
s.class(ww\$co, ardeche\$sta.fac, clab = 1.5, cell = 0, axesell = FALSE)
s.label(ww\$co, add.p = TRUE, clab = 0.75)
}

witwitsepan(ww, c(4, 6))
```

ade4 documentation built on Feb. 16, 2023, 7:58 p.m.