sim9.fast

Usage

sim9(speciesData, algo, metric, nReps = 1000, rowNames = TRUE, saveSeed = FALSE, burn_in = 0)

Arguments

speciesData

a dataframe in which rows are species, columns are sites, and the entries indicate the absence (0) or presence (1) of a species in a site. Empty rows and empty columns should not be included in the matrix.

algo

the algorithm to use, must be "sim1", "sim2", "sim3", "sim4", "sim5", "sim6", "sim7", "sim8", "sim9", "sim10"

metric

the metric used to caluclate the null model: choices are "species_combo", "checker", "c_score", "c_score_var", "c_score_skew", "v_ratio"; default is "c_score"

nReps

the number of replicates to run the null model.

rowNames

Does your dataframe have row names? If yes, they are stripped, otherwise FALSE for data that has no row names

saveSeed

TRUE or FALSE. If TRUE the current seed is saved so the simulation can be repeated

burn_in

The number of burn_in iterations to use with the simFast algorithm

algoOpts

a list containing all the options for the specific algorithm you want to use. Must match the algorithm given in the `algo` argument

metricOpts

a list containing all the options for the specific metric you want to use. Must match the metric given in the `metric` argument

Examples

## <strong>Not run</strong>: 
# 
# ## Run the null model
# finchMod <- cooc_null_model(dataWiFinches, algo="sim1",nReps=1000000,burn_in = 500)
# ## Summary and plot info
# summary(finchMod)
# plot(finchMod,type="burn_in")
# plot(finchMod,type="hist")
# plot(finchMod,type="cooc")
# ## <strong>End(Not run)</strong>