cooc_null_model: Co-Occurrence Null model
In EcoSimR: Null Model Analysis for Ecological Data

Create a Co-Occurrence null model

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

`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'.

## Not run: 

## 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$Sim)

finchMod <- cooc_null_model(dataWiFinches, algo="sim1")
## Check model output is the same as before
mean(finchMod$Sim)
reproduce_model(finchMod$Sim)



## End(Not run)