Traitspace (version 1.0)

pval: Permutation test on distances

Description

First calls the function distTraitspace to calculate the distances between the predicted and true/observed relative abundances (by default) or species distributions if byrow = FALSE. Then runs permutation tests to test if these distances are statistically significant and provides p-values.

Usage

pval(result, obs = NULL, byrow = TRUE, permutations = 999)

Arguments

result

the output from the traitspace function (class Traitspace)

obs

The observed matrix - where, each row corresponds to a site and each column to a species - the order of sites and species should match with the order in which they appear in the predicted matrix. By default, NULL, will generate the observed matrix using t

byrow

By default, TRUE, will compare the relative abundances. If FALSE, will compare the species distribution.

permutations

Number of permutations, by default 999.

Value

• A list of distances calculated using the following measures: Euclidean, Manhatten, Hellinger, Kullback-Leibler and Bhattacharya. It calculates both the average distance (averages across all sites or species) as well as individual distances. Also provides p-values corresponding to each of these distances.

References

Basu, A., Shioya, H., & Park, C. (2011). Statistical inference: the minimum distance approach. CRC Press. Phipson, B., & Smyth, G. K. (2010). Permutation p-values should never be zero: calculating exact P-values when permutations are randomly drawn. Statistical applications in genetics and molecular biology, 9(1).

See Also

distTraitspace, Traitspace, TraitspaceMod

Examples

data(spdata)
species<-spdata$species  #species column
trt<-cbind(spdata$t1,spdata$t2) #two traits
env<-spdata$env     #one env gradient
site<-spdata$site   #site information
result1<-Traitspace(species, trt, env, site)
pval(result1)