Articles | Volume 12, issue 5
https://doi.org/10.5194/cp-12-1215-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/cp-12-1215-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Technical note: Estimating unbiased transfer-function performances in spatially structured environments
Mathias Trachsel
CORRESPONDING AUTHOR
Department of Biology, University of Bergen, PO Box 7803,
5020 Bergen, Norway
currently at: Department of Geology, University of Maryland, College Park,
MD 20742, USA
Richard J. Telford
Department of Biology, University of Bergen, PO Box 7803,
5020 Bergen, Norway
Bjerknes Centre for Climate Research, Bergen,
Norway
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Latest update: 02 Nov 2024
Short summary
In spatially structured environments, conventional cross validation results in over-optimistic transfer function performance estimates. H-block cross validation, where all samples within h kilometres of the test samples are omitted is a method for obtaining unbiased transfer function performance estimates. We assess three methods for determining the optimal h using simulated data and published transfer functions. Some transfer functions perform notably worse when h-block cross validation is used.
In spatially structured environments, conventional cross validation results in over-optimistic...