collinear

0th

Percentile

Collinearity test

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

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.

Value

Messages and a vector of correlated variables

Aliases
  • collinear
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 ) 		       

# }
Documentation reproduced from package spatialEco, version 1.3-2, License: GPL-3

Community examples

Looks like there are no examples yet.