Re: [R] testing significance of axis loadings from multivariate dudi.mix

[Mark Difford]

On Nov 05, 2011 at 11:01pm Francisco Mora Ardila wrote:

> But a problem arised with the predict function: it doesn´t seem to work
> with an object 
> from dudi.mix and I dont understand why.

Francisco,

There is no predict() method for dudi.mix() or for any of the dudi objects
in ade4. I don't see why you can't get around this by doing something like
the following, but you need to take account of any scaling/centring that you
might do to your data before calling dudi.mix().

## Does a dudi.mix on continuous data, so really equals a
dudi.pca/princomp/PCA
library(ade4)
data(deug)
deug.dudi <- dudi.mix(deug$tab, scann=F, nf=2)
tt <- as.matrix(deug.dudi$tab) %*% as.matrix(deug.dudi$c1)  ## see note
below
qqplot(deug.dudi$li[,1], tt[,1])
qqplot(deug.dudi$li[,2], tt[,2])

deug.princ <- princomp(deug$tab, cor=T)
qqplot(predict(deug.princ)[,1], tt[,1])

## scaling not accounted for:
deug.princ <- princomp(deug$tab, cor=F)
qqplot(predict(deug.princ)[,1], tt[,1])

rm(tt, deug.dudi, deug.princ)

Note that in the code given above, "as.matrix(deug.dudi$tab) %*%
as.matrix(deug.dudi$c1)" is based on how stats:::predict.princomp does it.

Regards, Mark.




-
Mark Difford (Ph.D.)
Research Associate
Botany Department
Nelson Mandela Metropolitan University
Port Elizabeth, South Africa
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[R] testing significance of axis loadings from multivariate dudi.mix

[Francisco Mora Ardila]

Hi all

I´m trying to tests the significance of loadings from a ordination of 46 
variables 
(caategorical, ordinal and nominal). I used dudi.mix from ade4 for the 
ordination. A 
years ago Jari Oksanen wrote this script implementing Peres-Neto et al. 2003 
(Ecology) 
bootstraping method:



netoboot <- function (x, permutations=1000, ...) 
{

   pcnull <- princomp(x, cor = TRUE, ...) 
   res <- pcnull$loadings 
   out <- matrix(0, nrow=nrow(res), ncol=ncol(res))
   N <- nrow(x) 
   for (i in 1:permutations) {

   pc <- princomp(x[sample(N, replace=TRUE), ], cor = TRUE ...)
   pred <- predict(pc, newdata = x)
   r <-  cor(pcnull$scores, pred)
   k <- apply(abs(r), 2, which.max)
   reve <- sign(diag(r[k,]))
   sol <- pc$loadings[ ,k]
   sol <- sweep(sol, 2, reve, "*")
   out <- out + ifelse(res > 0, sol <=  0, sol >= 0)
   } 
   out/permutations 
}



I tried to aply it to the case of dudi.mix instead of princomp this way:




netoboot1<-function (x, permutations=1000,...) {

   dudinull <- dudi.mix(x, scannf = FALSE, nf = 3) 
   res <- dudinull$c1 
   out <- matrix(0, nrow=nrow(res), ncol=ncol(res))
   N <- nrow(x) 
   for (i in 1:permutations) {

   dudi <- dudi.mix(x[sample(N, replace=TRUE), ], scannf = FALSE, nf = 3)
   pred <- predict(dudi, newdata = x)
   r <-  cor(dudinull$li, pred) 
   k <- apply(abs(r), 2, which.max)
   reve <- sign(diag(r[k,]))
   sol <- dudi$c1[ ,k]
   sol <- sweep(sol, 2, reve, "*")
   out <- out + ifelse(res > 0, sol <=  0, sol >= 0)
   } 
   out/permutations 
}

But a problem arised with the predict function: it doesn´t seem to work with an 
object 
from dudi.mix and I dont understand why. Can somebody tell me why? Any 
suggestions to 
modify the script or to use other method?

Thanks in advance.

Francisco

Francisco Mora Ardila
Laboratorio de Biodiversidad y Funcionamiento del Ecosistema
Centro de Investigaciones en Ecosistemas
UNAM-Campus Morelia
Tel 3222777 ext. 42621
Morelia , MIchoacán, México.

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