Duality Diagram

Description

`as.dudi` is called by many functions (`dudi.pca`, `dudi.coa`, `dudi.acm`, ...) and not directly by the user. It creates duality diagrams.

`t.dudi` returns an object of class '`dudi`' where the rows are the columns and the columns are the rows of the initial `dudi`.

`is.dudi` returns TRUE if the object is of class `dudi`

`redo.dudi` computes again an analysis, eventually changing the number of kept axes. Used by other functions.

Usage

```as.dudi(df, col.w, row.w, scannf, nf, call, type, tol = 1e-07,
full = FALSE)
## S3 method for class 'dudi':
print(x, ...)
is.dudi(x)
redo.dudi(dudi, newnf = 2)
## S3 method for class 'dudi':
t(x)
```

Arguments

 `df` a data frame with n rows and p columns `col.w` a numeric vector containing the row weights `row.w` a numeric vector containing the column weights `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 `call` generally `match.call()` `type` a string of characters : the returned list will be of class `c(type, "dudi")` `tol` a tolerance threshold for null eigenvalues (a value less than tol times the first one is considered as null) `full` a logical value indicating whether all non null eigenvalues should be kept `x, dudi` objects of class `dudi` `...` further arguments passed to or from other methods `newnf` an integer indicating the number of kept axes

Value

as.dudi and all the functions that use it return a list with the following components :
 `tab` a data frame with n rows and p columns `cw` column weights, a vector with n components `lw` row (lines) weights, a vector with p components `eig` eigenvalues, a vector with min(n,p) components `nf` integer, number of kept axes `c1` principal axes, data frame with p rows and nf columns `l1` principal components, data frame with n rows and nf columns `co` column coordinates, data frame with p rows and nf columns `li` row coordinates, data frame with n rows and nf columns `call` original call

Author(s)

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

References

Escoufier, Y. (1987) The duality diagram : a means of better practical applications In Development in numerical ecology, Legendre, P. & Legendre, L. (Eds.) NATO advanced Institute, Serie G. Springer Verlag, Berlin, 139–156.

Examples

```data(deug)
dd1 <- dudi.pca(deug\$tab, scannf = FALSE)
dd1
t(dd1)
is.dudi(dd1)
redo.dudi(dd1,3)
```

Worked out examples

```
> ### Name: dudi
> ### Title: Duality Diagram
> ### Aliases: dudi as.dudi print.dudi t.dudi is.dudi redo.dudi
> ### Keywords: multivariate
>
> ### ** Examples
>
> data(deug)
> dd1 <- dudi.pca(deug\$tab, scannf = FALSE)
> dd1
Duality diagramm
class: pca dudi
\$call: dudi.pca(df = deug\$tab, scannf = FALSE)

\$nf: 2 axis-components saved
\$rank: 9
eigen values: 3.101 1.363 1.032 0.9341 0.7398 ...
vector length mode    content
1 \$cw    9      numeric column weights
2 \$lw    104    numeric row weights
3 \$eig   9      numeric eigen values

data.frame nrow ncol content
1 \$tab       104  9    modified array
2 \$li        104  2    row coordinates
3 \$l1        104  2    row normed scores
4 \$co        9    2    column coordinates
5 \$c1        9    2    column normed scores
other elements: cent norm
> t(dd1)
Duality diagramm
class: transpo dudi
\$call: t.dudi(x = dd1)

\$nf: 2 axis-components saved
\$rank: 9
eigen values: 3.101 1.363 1.032 0.9341 0.7398 ...
vector length mode    content
1 \$cw    104    numeric column weights
2 \$lw    9      numeric row weights
3 \$eig   9      numeric eigen values

data.frame nrow ncol content
1 \$tab       9    104  modified array
2 \$li        9    2    row coordinates
3 \$l1        9    2    row normed scores
4 \$co        104  2    column coordinates
5 \$c1        104  2    column normed scores
other elements: NULL
> is.dudi(dd1)
[1] TRUE
> redo.dudi(dd1,3)
Duality diagramm
class: pca dudi
\$call: dudi.pca(df = deug\$tab, scannf = FALSE, nf = 3)

\$nf: 3 axis-components saved
\$rank: 9
eigen values: 3.101 1.363 1.032 0.9341 0.7398 ...
vector length mode    content
1 \$cw    9      numeric column weights
2 \$lw    104    numeric row weights
3 \$eig   9      numeric eigen values

data.frame nrow ncol content
1 \$tab       104  9    modified array
2 \$li        104  3    row coordinates
3 \$l1        104  3    row normed scores
4 \$co        9    3    column coordinates
5 \$c1        9    3    column normed scores
other elements: cent norm
>
>
>
>
```