Displaying 3 results from an estimated 3 matches for "pcnull".
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2009 Jan 19
3
bootstrapped eigenvector method following prcomp
...mber of
loadings =<0 for loadings that were negative in the original matrix
divided by the number of boostrap samples (1000)."
(see https://stat.ethz.ch/pipermail/r-help/2005-January/065139.html ).
The suggested solution (by Jari Oksanen) was
function (x, permutations=1000, ...)
{
pcnull <- princomp(x, ...)
res <- pcnull$loadings
out <- matrix(0, nrow=nrow(res), ncol=ncol(res))
N <- nrow(x)
for (i in 1:permutations) {
pc <- princomp(x[sample(N, replace=TRUE), ], ...)
pred <- predict(pc, newdata = x)
r <- cor(pcnull$score...
2011 Nov 05
1
testing significance of axis loadings from multivariate dudi.mix
...oadings 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 <...
2005 Jan 29
1
Bootstrapped eigenvector
Hello alls,
I found in the literature a technique that has been evaluated as one of the
more robust to assess statistically the significance of the loadings in a
PCA: bootstrapping the eigenvector (Jackson, Ecology 1993, 74: 2204-2214;
Peres-Neto and al. 2003. Ecology 84:2347-2363). However, I'm not able to
transform by myself the following steps into a R program, yet?
Can someone could help