vf {ecodist} R Documentation

## Vector fitting

### Description

Fits ancillary variables to an ordination configuration.

### Usage

vf(ord, vars, nperm = 100)


### Arguments

 ord matrix containing a 2-dimensional ordination result with axes as columns. vars matrix with ancillary variables as columns. nperm number of permutation for the significance test. If nperm = 0, the test will be omitted.

### Details

Vector fitting finds the maximum correlation of the individual variables with a configuration of samples in ordination space.

### Value

an object of class vf containing matrix with the first 2 columns containing the scores for every variable in each of the 2 dimensions of the ordination space. r is the maximum correlation of the variable with the ordination space, and pval is the result of the permutation test.

Sarah Goslee

### References

Jongman, R.H.G., C.J.F. ter Braak and O.F.R. van Tongeren. 1995. Data analysis in community and landscape ecology. Cambridge University Press, New York.

plot.vf

### Examples


# Example of multivariate analysis using built-in iris dataset
data(iris)
iris.d <- dist(iris[,1:4])

### nmds() is timeconsuming, so this was generated
### set.seed(1234)
### iris.nmds <- nmds(iris.d, nits=20, mindim=1, maxdim=4)
### save(iris.nmds, file="ecodist/data/iris.nmds.rda")
data(iris.nmds)

# examine fit by number of dimensions
plot(iris.nmds)

# choose the best two-dimensional solution to work with
iris.nmin <- min(iris.nmds, dims=2)

# fit the data to the ordination as vectors
### vf() is timeconsuming, so this was generated
plot(iris.nmin, col=as.numeric(iris$Species), pch=as.numeric(iris$Species), main="NMDS")