runNulls: Randomize input CDM according to defined null models
In metricTester: Test Metric and Null Model Statistical Performance

Description Usage Arguments Details Value References Examples

Given a prepared nulls.input object, will randomize a community data matrix according to specified null models, and return a list of randomized CDMs.

1	runNulls(nulls.input, nulls, new_ = FALSE)

`nulls.input`	Prepped nulls.input object
`nulls`	Optional. If not provided, defines the nulls as all of those in defineNulls. If only a subset of those is desired, then nulls should take the form of a character vector corresponding to named functions from defineNulls. The available nulls can be determined by running names(defineNulls()). Otherwise, if the user would like to define a new null on the fly, the argument nulls can take the form of a named list of new functions (nulls). If the latter, new_ must be set to TRUE.
`new_`	Whether or not new nulls are being defined on the fly. Default is FALSE. Set to TRUE if a new null is being used.

Determine which nulls will be calculated by running names(defineNulls()). If only a subset of these is desired, supply metrics with a character vector of the named, available metrics.

A list of matrices. Each matrix is a product of a randomization of the input CDM and one of the specified null models.

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

#simulate tree with birth-death process
tree <- geiger::sim.bdtree(b=0.1, d=0, stop="taxa", n=50)

sim.abundances <- round(rlnorm(5000, meanlog=2, sdlog=1)) + 1

cdm <- simulateComm(tree, richness.vector=10:25, abundances=sim.abundances)

prepped <- prepNulls(tree, cdm)

results <- runNulls(prepped)