filter_vif {AICcPermanova}

Filters out equations with high multicollinearity

Description

This function takes a dataframe with several models and calculates the maximum Variance Inflation Factor (VIF) for a given model. And either filters out the ones with high collinearity or it flags them accordingly

Usage

filter_vif(all_forms, env_data, ncores = 2, filter = TRUE, verbose = TRUE)

Arguments

all_forms

A data frame generated by make_models

env_data

A dataset with the variables described in all_froms

ncores

An integer specifying the number of cores to use for parallel processing

filter

logical, if TRUE it filters out the models with a maximum VIF of high or higher, if FALSE it generates a new column called collinearity, wich will

verbose

logical, defaults TRUE, sends messages about processing times

Value

A data.frame with the models, fitering out the ones with high collinearity or flagginf them.

Examples

library(vegan)
data(dune)
data(dune.env)
AllModels <- make_models(vars = c("A1", "Moisture", "Manure"))

filter_vif(all_forms = AllModels,
           env_data = dune.env)