Multivariate discriminant analysis of sub-Antarctic Deep-Sea sediments

• Main Authors: Huang, T. C., Ellwood, B. B., Hanumara, R. C.
• Format: Text
• Language: unknown
• Published: LSU Digital Commons 1974
• Subjects: Automatic data processing; Deep-sea sediment; Discriminant analysis; Antarctic; Antarc*
• Online Access: https://digitalcommons.lsu.edu/geo_pubs/878; https://doi.org/10.1130/0016-7606(1974)85<1821:MDAOSD>2.0.CO;2

Multivariate discriminant analysis of sediment grain-size data from a series of sub-Antarctic deep-sea sedimentary cores has yielded equations which differentiate between terrigenous, siliceous, and calcareous components. As a test of the methods, grain-size distribution data for 106 specimens from two sedimentary cores were examined using discriminant-predictive equations. A modified discriminant technique is used. The predicted sediment groups for these samples are in good agreement with independent microscopic observations. It is proposed that multivariate discriminant analysis of grain-size data provides automated data collection and rapid diagnosis of sedimentary type for restricted regions. This, in turn, facilitates genetic interpretations of sedimentary texture and depositional processes. © 1974 Geological Society of America.