Hi all, I'm curious what your recommendations would be for how best to add a
covariate to a (Self-Exciting) Threshold AutoRegressive model in R. I've
looked at both the "setar" function of the tsDyn-package and the "tar"
function of the TSA-package, none of which, with my limited experience in
run
Anything where you are interested in the centroid moving in
compositional space is handled by `adonis()` at least for testing if the
change is significant.
betadisper() handles the case when you want to know if the spread about
the centroid is changing.
Neither do what you want in total I don't t
Thanks Gavin. Let me try to explain what Im trying to do.
My data are hierarchically structured, I have subplots within sites and
these subplots are measured over many years. I want to compare how
vegetation composition varies over time at the site level (a bit like
the example in Zuur 2007, p
Dear List,
I am looking to cluster data, with the data being coefficients from a
regression (subsets)
The "NA" represent variables that were not present in the most likely model (
based on AIC), and the value the magnitude and direction of the relationship.
I would like to cluster the data so
betadisper() will give you a test of homogeneity of variance between
groups; in other words it tests the null that the variance of the groups
of sites does not change. adonis() is a test of location, which will
test the null of no compositional change between groups of sites. Here I
assume by group
