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MAT for many environmental variables simultaneously. More efficient than calculating them separately for each variable.
multi.mat( training.spp, envs, core.spp, noanalogues = 10, method = "sq-chord", run = "both" )
If run = "both", a list with two elements:
run = "both"
Matrix of leave-one-out cross-validation predictions for the calibration set
Matrix of predictions for the fossil data
Otherwise, one of these matrices is returned.
Community data
Environmental variables - or simulations
Optional fossil data to make predictions for
Number of analogues to use
distance metric to use
Return LOO predictions or predictions for fossil data
Richard Telford Richard.Telford@bio.uib.no
Telford, R. J. and Birks, H. J. B. (2009) Evaluation of transfer functions in spatially structured environments. Quaternary Science Reviews 28: 1309--1316. tools:::Rd_expr_doi("10.1016/j.quascirev.2008.12.020")
data(arctic.env) data(arctic.pollen) mMAT <- multi.mat(arctic.pollen, arctic.env[, 9:67], noanalogues = 5)
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