| ccm {labdsv} | R Documentation |
Community Composition Modeling
Description
Compares the composition of modeled communities to real data using Bray-Curtis similarity
Usage
ccm(model,data)Arguments
model |
fitted data from a predictive model |
data |
actual data from the modeled communities |
Details
The algorithm sweeps through the fitted values and data one sample unit at time calculating the similarity to the simulated community to the real community. The calculation is similarity, not dissimilarity, and results in a vector of length equal to the number of sample units.
The diverse matrix has the diversity of the data in the first column, and the diversity of the simulated or fitted data in the second column.
Value
A list object with two components:
sim |
a vector of similarities of modeled communities to actual data |
diverse |
Shannon-Weaver diversity values for modeled and real data |
Author(s)
David W. Roberts droberts@montana.edu
Examples
data(bryceveg)
bryceveg <- dropspc(bryceveg,4)
bryce.bc <- dsvdis(bryceveg,'bray')
bryce.nmds <- nmds(bryce.bc)
## Not run: bryce.preds <- predict(bryce.nmds,bryceveg)
## Not run: bryce.ccm <- ccm(bryceveg,bryce.preds$fitted)
## Not run: summary(bryce.ccm$sim)
## Not run: boxplot(bryce.ccm$diverse)