Simplifying compositional multiple regression: Application to grain size controls on sediment geochemistry

Modern geochemical data sets have typically around 20–30 compositional variables measured on some tens or hundreds of samples. A statistical analysis of data sets with so many variables should take as a priority the reduction of dimensionality of the model, in order to increase its reliability and e...

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Veröffentlicht in:	Computers & geosciences 2010-05, Vol.36 (5), p.577-589
Hauptverfasser:	Tolosana-Delgado, R., von Eynatten, H.
Format:	Artikel
Sprache:	eng
Schlagworte:	Clay minerals Comminution Earth sciences Earth, ocean, space Exact sciences and technology Grain size Isometric log-ratio transformation Mathematical analysis Mathematical models Sand Sedimentary petrology Statistical analysis Statistical methods Step functions Weathering
Online-Zugang:	Volltext
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