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
Stephane 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 1.7-4 Index]