metricTester (version 1.2.2)

metricPerformance: Summarize metric performance of a series of summarized simulation results

Description

Flexible function that summarizes metric performance after reading in and testing simulation results with either sesIndiv or plotOverall.

Usage

metricPerformance(summarized.results, simulations = "all", nulls = "all", concat.by = "both")

Arguments

summarized.results

The results of a call to sesIndiv() or plotOverall()

simulations

Default is "all". Alternatively, can supply a vector of simulation names to summarize the results over.

nulls

Default is "all". Alternatively, can supply a vector of null model names to summarize the results over.

concat.by

Default is "both". Alternatively, can supply either "plot" or "richness".

Value

A data frame of summarized results

Details

If an overall picture of metric performance is desired, this function can provide it. It can also be used to summarize metric performance over a specific subset of simulations, null models, and concatenation options. If provided with the results of a call to plotOverall, the options are more limited. Currently, if provided with such a result, the assumption is that there are three spatial simulations, "random", "filtering", and "competition". It then assumes that any clustered or overdispersed plots for the random simulation, or any overdispersed or clustered for the filtering or competition simulations, respectively, count as typeI errors. It assumes that any plots that are not clustered or overdispersed for the filtering or competition simulations, respectively, count as typeII errors.

References

Miller, E. T., D. R. Farine, and C. H. Trisos. 2015. Phylogenetic community structure metrics and null models: a review with new methods and software. bioRxiv 025726.

Examples

#not run
#results <- readIn()
#summ <- sesIndiv(results)
#examp <- metricPerformance(summ)