cor2m {ecodist} | R Documentation |
Generate a correlation table between the variables of two data sets, originally for comparing species abundances and environmental variables.
cor2m(x, y, trim = TRUE, alpha = 0.05)
x |
A matrix or data frame of environmental (or other) variables matching the sites of x |
y |
A matrix or data frame of species (or other) variables |
trim |
If trim is TRUE, set rho<critical value(alpha) to 0 |
alpha |
alpha p-value to use with trim, by default 0.05 |
cor2m generates a correlation table between the variables of two matrices. The original use case is to compare species abundances and environmental variables. It results in a data frame with species (or the first matrix) as columns and environmental variables (or the second matrix) as rows, so it's easy to scan. Correlations less than a user-specified alpha (0.05 by default) can be set to NA. cor2m generates a correlation table between the variables of two matrices. The original use case is to compare species abundances and environmental variables. The result has species (or the first matrix) as columns and environmental variables (or the second matrix) as rows, so it's easy to scan. Correlations less than a user-specified alpha can be set to NA. If trim, correlations less than the critical value for the provided alpha are set to to NA. The critical value is computed as a t-test with n-2 df. cor2m(x, y, trim=FALSE) is equivalent to cor(x, y)
Returns a data frame of correlations between the variables of 2 data frames.
Dean Urban
data(graze)
speciesdata <- graze[, 3:7]
envdata <- graze[, 1:2]
sppenv.cor <- cor2m(envdata, speciesdata)
print(sppenv.cor, na.print="")