Environmental Distribution Test
Calculates whether the value of a specified environmental variable has an improbable distribution with respect to a specified vector
envrtest(set,env,numitr=1000,minval=0,replace=FALSE,
plotit = TRUE, main = paste(deparse(substitute(set)),
" on ", deparse(substitute(env))))set |
a vector of logical or quantitative values |
env |
the quantitative variable whose distribution is to be tested |
numitr |
the number of randomizations to iterate to calculate probabilities |
minval |
the threshold to use to partition the data into a logical if set is quantitative |
replace |
whether to permute (replace=FALSE) or bootstrap (replace=TRUE) the values in the permutation test |
plotit |
logical; plot results if TRUE |
main |
title for plot if plotted |
Calculates the maximum within-set difference in the values of vector ‘env’, and the distribution of the permuted random within-set differences. It then plots the observed difference as a red line, and the sorted permuted differences as a black line and prints the probability of getting such a limited distribution. The probability is calculated by permuting numitr-1 times, counting the number of times the permuted maximum difference is as small or smaller than observed (n), and calculating (n+1)/numitr. To get three-digit probabilities, set numitr=1000 (the default)
Produces a plot on the current graphics device, and an invisible list with the components observed within-set difference and the p-value.
The plot is based on the concept of constraint, or limiting value, and checks to see whether the distribution of a particular variable within a cluster is constrained in an improbable way.
data(bryceveg) # returns a vegetation data.frame data(brycesite) # returns and environmental data.frame envrtest(bryceveg$berrep>0,brycesite$elev)
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