R: Double principal coordinate analysis

dpcoa {ade4} | R Documentation

## Double principal coordinate analysis

### Description

Performs a double principal coordinate analysis

### Usage

    dpcoa(df, dis = NULL, scannf = TRUE, nf = 2, full = FALSE, tol = 1e-07,
    RaoDecomp = TRUE)
    ## S3 method for class 'dpcoa'
    plot(x, xax = 1, yax = 2, ...)
    ## S3 method for class 'dpcoa'
     print(x, ...)
    ## S3 method for class 'dpcoa'
     summary(object, ...)

### Arguments

`df` | a data frame with samples as rows and categories (i.e. species) as columns and abundance or presence-absence as entries. Previous releases of ade4 (<=1.6-2) considered the transposed matrix as argument.
`dis` | an object of class `dist` containing the distances between the categories.
`scannf` | a logical value indicating whether the eigenvalues bar plot should be displayed
`RaoDecomp` | a logical value indicating whether Rao diversity decomposition should be performed
`nf` | if scannf is FALSE, an integer indicating the number of kept axes
`full` | a logical value indicating whether all non null eigenvalues should be kept
`tol` | a tolerance threshold for null eigenvalues (a value less than tol times the first one is considered as null)
`x, object` | an object of class `dpcoa`
`xax` | the column number for the x-axis
`yax` | the column number for the y-axis
`...` | `...` further arguments passed to or from other methods

### Value

Returns a list of class `dpcoa` containing:

`call` | call
`nf` | a numeric value indicating the number of kept axes
`dw` | a numeric vector containing the weights of the elements (was `w1` in previous releases of ade4)
`lw` | a numeric vector containing the weights of the samples (was `w2` in previous releases of ade4)
`eig` | a numeric vector with all the eigenvalues
`RaoDiv` | a numeric vector containing diversities within samples
`RaoDis` | an object of class `dist` containing the dissimilarities between samples
`RaoDecodiv` | a data frame with the decomposition of the diversity
`dls` | a data frame with the coordinates of the elements (was `l1` in previous releases of ade4)
`li` | a data frame with the coordinates of the samples (was `l2` in previous releases of ade4)
`c1` | a data frame with the scores of the principal axes of the elements

### Author(s)

Daniel Chessel
Sandrine Pavoine pavoine@mnhn.fr
Stéphane Dray stephane.dray@univ-lyon1.fr

### References

Pavoine, S., Dufour, A.B. and Chessel, D. (2004) From dissimilarities among species to dissimilarities among communities: a double principal coordinate analysis. Journal of Theoretical Biology, 228, 523–537.

### Examples

    data(humDNAm)
    dpcoahum <- dpcoa(data.frame(t(humDNAm$samples)), sqrt(humDNAm$distances), scan = FALSE, nf = 2)
    dpcoahum
    if(adegraphicsLoaded()) {
      g1 <- plot(dpcoahum)
    } else {
      plot(dpcoahum)
    }

    ## Not run:
    data(ecomor)
    dtaxo <- dist.taxo(ecomor$taxo)
    dpcoaeco <- dpcoa(data.frame(t(ecomor$habitat)), dtaxo, scan = FALSE, nf = 2)
    dpcoaeco

    if(adegraphicsLoaded()) {
      g1 <- plot(dpcoaeco)
    } else {
      plot(dpcoaeco)
    }

    ## End(Not run)

[Package ade4 version 1.7-15 Index]