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Transfer Functions for Paleoclimate Reconstructions — Theory and Methods

  • Thomas Kumke
  • Christian Schölzel
  • Andreas Hense
Part of the GKSS School of Environmental Research book series (GKSS)

Summary

In this chapter, all within the KIHZ-community used methods for deriving transfer functions in order to reconstruct paleoclimatic variables are introduced. The aim is to provide the conceptual and statistical background of the methods which are used throughout this book. A short review is given on the use of probability density functions in paleoecology. We then focus on linear and non-linear regression methods, among them are weighted averaging, weighted averaging partial least squares regression, both frequently used in paleolimnology, as well as neural network regression, which is recently used in pollen-based paleoclimate reconstructions. In addition, we review some of the validation methods for transfer functions.

Keywords

Transfer Function Partial Little Square Plant Functional Type Pollen Taxon Neural Network Regression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Thomas Kumke
  • Christian Schölzel
  • Andreas Hense

There are no affiliations available

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