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5.13 Sphericising variables
It was previously stated that CAP effectively “sphericises” the data clouds as part of the proces...
5.12 Canonical correlation: multiple X’s
In some cases, interest lies in finding axes through the cloud of points so as to maximise correl...
5.11 Canonical correlation: single gradient (Fal estuary biota)
So far, the focus has been on hypotheses concerning groups and the use of CAP for discriminant an...
5.10 Adding new samples
A new utility of the windows-based version of the CAP routine in PERMANOVA+ is the ability to pla...
5.8 CAP versus PERMANOVA
It might seem confusing that both CAP and PERMANOVA can be used to test for differences among gro...
5.7 Test by permutation (Anderson’s irises)
CAP can be used to test for significant differences among the groups in multivariate space. The t...
5.5 Diagnostics
How did the CAP routine choose an appropriate number of PCO axes to use for the above discriminan...
5.4 Discriminant analysis (Poor Knights Islands fish)
We will begin with an example provided by Trevor Willis and Chris Denny (; ), examining temperate...
5.3 Mechanics of CAP
Details of CAP and how it is related to other methods are provided by and . In brief, a classica...
4.16 DISTLM versus BEST/ BIOENV
On the face of it, the DISTLM routine might be thought of as playing a similar role to PRIMER’s B...
4.15 Categorical predictor variables (Oribatid mites)
Sometimes the predictor variables of interest are not quantitative, continuous variables, but rat...
4.14 Analysing variables in sets (Thau lagoon bacteria)
In some situations, it is useful to be able to partition variability in the data cloud according ...
4.13 dbRDA plot for Ekofisk
Let us examine the constrained dbRDA ordination for the parsimonious model obtained earlier using...
4.12 Vector overlays in dbRDA
Something which certainly should come as no surprise is to see the X variables playing an importa...
4.11 Visualising models: dbRDA
We may wish to visualise a given model in the multivariate space of our chosen resemblance matrix...
4.10 (Ekofisk macrofauna)
We shall now use the DISTLM tool to identify potential parsimonious models for benthic macrofauna...
4.8 Building models
In many situations, a scientist may have measured a large number of predictor variables that coul...
4.7 Assumptions & diagnostics
Thus far, we have only done examples for a univariate response variable in Euclidean space, using...
4.6 (Holdfast invertebrates)
To demonstrate conditional tests in DISTLM, we will consider the number of species inhabiting hol...
1.13 PERMANOVA versus ANOSIM
The analysis of similarities (ANOSIM), described by is also available within PRIMER and can be u...