Co-Occurrence Null model

Usage

cooc_null_model(speciesData, algo = "sim9", metric = "c_score", nReps = 1000, saveSeed = FALSE, burn_in = 500, algoOpts = list(), metricOpts = list(), suppressProg = FALSE)

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"; default is "sim9".
metric
the metric used to calculate 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 replicate null assemblages to create; default is 1000 replicates.
saveSeed
TRUE or FALSE. If TRUE the current seed is saved so the simulation can be repeated; default is FALSE.
burn_in
The number of burn_in iterations to use with the simFast algorithm; default is 500 burn-in replicates.
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.
suppressProg
TRUE or FALSE. If true, display of the progress bar in the console is suppressed; default is FALSE. This setting is useful for creating markdown documents with `knitr`.

Description

Create a Co-Occurrence null model

Examples

## <strong>Not run</strong>: # ## Run the null model # finchMod <- cooc_null_model(dataWiFinches, algo="sim9",nReps=10000,burn_in = 500) # ## Summary and plot info # summary(finchMod) # plot(finchMod,type="burn_in") # plot(finchMod,type="hist") # plot(finchMod,type="cooc") # # ## Example that is repeatable with a saved seed # finchMod <- cooc_null_model(dataWiFinches, algo="sim1",saveSeed = TRUE) # mean(finchMod$Sim) # ## Run the model with the seed saved # # finchMod <- cooc_null_model(dataWiFinches, algo="sim1",saveSeed=T) # ## Check model output # mean(finchMod$Sim) # # reproduce_model(finchMod) # # finchMod <- cooc_null_model(dataWiFinches, algo="sim1") # ## Check model output is the same as before # mean(finchMod$Sim) # reproduce_model(finchMod) # # ## <strong>End(Not run)</strong>