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Research ArticleArticles

A data-driven spline model designed to predict paleoclimate using paleosol geochemistry

Gary E. Stinchcomb, Lee C. Nordt, Steven G. Driese, William E. Lukens, Forrest C. Williamson and Jack D. Tubbs
American Journal of Science October 2016, 316 (8) 746-777; DOI: https://doi.org/10.2475/08.2016.02
Gary E. Stinchcomb
* Watershed Studies Institute & Department of Geosciences, Murray State University, Murray, Kentucky 42071
** Terrestrial Paleoclimatology Research Group, Department of Geosciences, Baylor University, Waco, Texas 76798
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  • For correspondence: gstinchcomb@murraystate.edu
Lee C. Nordt
** Terrestrial Paleoclimatology Research Group, Department of Geosciences, Baylor University, Waco, Texas 76798
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Steven G. Driese
** Terrestrial Paleoclimatology Research Group, Department of Geosciences, Baylor University, Waco, Texas 76798
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William E. Lukens
** Terrestrial Paleoclimatology Research Group, Department of Geosciences, Baylor University, Waco, Texas 76798
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Forrest C. Williamson
*** Department of Statistical Science, Baylor University, Waco, Texas 76798
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Jack D. Tubbs
*** Department of Statistical Science, Baylor University, Waco, Texas 76798
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American Journal of Science: 316 (8)
American Journal of Science
Vol. 316, Issue 8
1 Oct 2016
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A data-driven spline model designed to predict paleoclimate using paleosol geochemistry
Gary E. Stinchcomb, Lee C. Nordt, Steven G. Driese, William E. Lukens, Forrest C. Williamson, Jack D. Tubbs
American Journal of Science Oct 2016, 316 (8) 746-777; DOI: 10.2475/08.2016.02

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A data-driven spline model designed to predict paleoclimate using paleosol geochemistry
Gary E. Stinchcomb, Lee C. Nordt, Steven G. Driese, William E. Lukens, Forrest C. Williamson, Jack D. Tubbs
American Journal of Science Oct 2016, 316 (8) 746-777; DOI: 10.2475/08.2016.02
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Keywords

  • weathering model
  • climosequence
  • soil geochemistry
  • Partial Least Squares

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