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labdsv (version 2.0-1)

ordtest: Ordination Distribution Test

Description

Testing the distribution of points in an ordination

Usage

ordtest(ord, var, dim=1:ncol(ord$points), index = 'euclidean',
   nitr = 1000)

Value

Produces a list with components:

obs

the observed sum of within-set distances

p

the probability of obtaining a value that small

reps

the sum of within-set pairwise distances for all permutations

Arguments

ord

an object of class ‘dsvord’

var

a logical or factor vector used to organize the calculation of within-set distances

dim

the number of dimensions to use in the calculation

index

the distance metric for the calculation of within-set distances. Currently only euclidean is accepted

nitr

the number of iterations to perform to establish p-values

Details

Calculates the sum of within-set pair-wise distances and compares to ‘nitr’ permutations of the same distribution to calculate the probability of observing clusters as tight as observed or tighter. The p-value is calculated by running nitr-1 permutations and counting the number of cases where the sum of pair-wise distances is as small as smaller than observed. That count is increased by one and divided by nitr to estimate p.

See Also

anosim

Examples

Run this code
data(bryceveg)
data(brycesite)
dis.bc <- dsvdis(bryceveg,'bray/curtis')
pco.bc <- pco(dis.bc)
plot(pco.bc)
demo <- ordtest(pco.bc,brycesite$quad)
demo$p

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