dpcoa {ade4}  R Documentation 
Performs a double principal coordinate analysis
dpcoa(df, dis = NULL, scannf = TRUE, nf = 2, full = FALSE, tol = 1e07, 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, ...)
df 
a data frame with samples as rows and categories (i.e. species) as columns and abundance or presenceabsence as entries. Previous releases of ade4 (<=1.62) considered the transposed matrix as argument. 
dis 
an object of class 
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 
xax 
the column number for the xaxis 
yax 
the column number for the yaxis 
... 

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

lw 
a numeric vector containing the weights of the samples (was

eig 
a numeric vector with all the eigenvalues 
RaoDiv 
a numeric vector containing diversities within samples 
RaoDis 
an object of class 
RaoDecodiv 
a data frame with the decomposition of the diversity 
dls 
a data frame with the coordinates of the elements (was

li 
a data frame with the coordinates of the samples (was

c1 
a data frame with the scores of the principal axes of the elements 
Daniel Chessel
Sandrine Pavoine pavoine@mnhn.fr
Stephane Dray stephane.dray@univlyon1.fr
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.
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)