metricTester (version 1.3.6)

betaErrorChecker: Wrapper for summarizing error rates of beta metric randomizations

Description

Given the results of a single iteration of the betaLinker function, returns a list of data frames summarizing the type I and II error rates of metrics both at the single plot and the entire arena level.

Usage

betaErrorChecker(single.iteration)

Arguments

single.iteration

Results of a run of the betaLinker function.

Value

A list of lists of matrices. The first element of the lists refers to the results from a spatial simulation. Within each of these elements is a list of matrices, where each matrix tabulates the error rate of all tested beta diversity metrics with a given null model.

Details

This function wraps a number of smaller functions into a useful type I and II error checker. It takes a reduced list of randomizations such as those reduced from metricsNnulls with reduceRandomizations, summarizes the mean, SD, and CI of each metric plus null model either at the richness or plot level, then compares the observed metric scores to those summarized metrics. It return a list with two elements. The first is a list of data frames, where each corresponds to the standardized effect scores of the observed metrics for a given null model. The second is a list of data frames, where each corresponds to whether a given plot deviates beyond CI. For the latter, 0 corresponds to within CI, 1 corresponds to less than the CI, and 2 corresponds to greater than the CI.

References

Miller, E. T., D. R. Farine, and C. H. Trisos. 2016. Phylogenetic community structure metrics and null models: a review with new methods and software. Ecography DOI: 10.1111/ecog.02070

Examples

# NOT RUN {
#run the betaLinker function
#below not run for timing issues on CRAN
#system.time(ex <- betaLinker(no.taxa=50, arena.length=300, mean.log.individuals=2, 
#length.parameter=5000, sd.parameter=50, max.distance=30, proportion.killed=0.2, 
#competition.iterations=3, no.plots=15, plot.length=30,
#randomizations=3, cores="seq",
#nulls=c("richness", "frequency")))

#test <- betaErrorChecker(ex)
# }