MAT for many environmental variables simultaneously. More efficient than calculating them separately for each variable.
Usage
multi.mat(training.spp, envs, core.spp, noanalogues = 10, method = "sq-chord",
run = "both")
Arguments
- training.spp
Community data
- envs
Environmental variables - or simulations
- core.spp
Optional fossil data to make predictions for
- noanalogues
Number of analogues to use
- method
distance metric to use
- run
Return LOO predictions or predictions for fossil data
Value
Matrix of predictions
References
Telford, R. J. and Birks, H. J. B. (2009) Evaluation of transfer functions in spatially structured environments. Quaternary Science Reviews 28: 1309–1316. doi:10.1016/j.quascirev.2008.12.020
Examples
data(arctic.env)
data(arctic.pollen)
mMAT <- multi.mat(arctic.pollen, arctic.env[,9:67], noanalogues = 5)