spatialEco (version 1.3-2)

collinear: Collinearity test

Description

Test for linear or nonlinear collinearity/correlation in data

Usage

collinear(x, p = 0.85, nonlinear = FALSE, p.value = 0.001)

Arguments

x

A data.frame or matrix containing continuous data

p

The correlation cutoff (default is 0.85)

nonlinear

A boolean flag for calculating nonlinear correlations (FALSE/TRUE)

p.value

If nonlinear is TRUE, the p value to accept as the significance of the correlation

Value

Messages and a vector of correlated variables

Details

Evaluation of the pairwise linear correlated variables to remove is accomplished through calculating the mean correlations of each variable and selecting the variable with higher mean.

Examples

# NOT RUN {
data(cor.data)

# Evaluate linear correlations on linear data
head( dat <- cor.data[[4]] ) 
pairs(dat, pch=20)
  ( cor.vars <- collinear( dat ) )

# Remove identified variable(s)
head( dat[,-which(names(dat) %in% cor.vars)] )

# Evaluate linear correlations on nonlinear data
#   using nonlinear correlation function
plot(cor.data[[1]], pch=20) 
  collinear(cor.data[[1]], p=0.80, nonlinear = TRUE ) 		       

# }