Usage
cooc_null_model(speciesData, algo = "sim9", metric = "c_score", nReps = 1000, rowNames = TRUE, saveSeed = FALSE, burn_in = 500, algoOpts = list(), metricOpts = list())
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
Description
Create a Co-Occurrence null model
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")
#
# ## 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)
#
#
# ## <strong>End(Not run)</strong>