Usage
null_model_engine(speciesData, algo, metric, nReps = 1000, rowNames = TRUE, saveSeed = FALSE, algoOpts = list(), metricOpts = list())
Arguments
- speciesData
- a dataframe
- algo
- the algorithm to use, must be "RA1", "RA2", "RA3", "RA4"
- metric
- the metric used to caluclate the null model: choices are "Pianka", "Czekanowski", "Pianka.var", "Czekanowski.var", "Pianka.skew", "Czekanowski.skew"; default is Pianka
- 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
- Should the existing random seed be saved to make the model reproducible?
- algoOpts
- a list containing options for a supplied alogrithm
- metricOpts
- a list containing options for a supplied metric
Description
This drives the null models for all the different kinds of null models that can be run. It is the underlying engine.