EcoSimR (version 0.1.0)

cooc_null_model: Co-Occurrence Null model

Description

Create a 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`.

Examples

## 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)