Comparison of two binomial models in probabilistic biostratigraphy

Author(s): Blank, Richard G.
Author Affiliation(s): Primary:
Strat. Serv. Co., Seattle, WA, United States
Volume Title: Theory, application and comparison of stratigraphic correlation methods; proceedings of IGCP Project 148 meeting
Volume Author(s): Agterberg, F. P., editor
Source: Computers & Geosciences, 10(1), p.59-67; Theory, application and comparison of stratigraphic correlation methods, Geneva, Switzerland, Nov. 22-23, 1982, edited by F. P. Agterberg. Publisher: Pergamon, New York-Oxford-Toronto, International. ISSN: 0098-3004 CODEN: GGEOD5
Note: In English. 16 refs.; illus. incl. 1 table, sketch map
Summary: Two statistical models have been applied to the same dataset: 295, Cenozoic and Mesozoic calcareous nannofossil taxa occurring at 55 geologic sections recovered by the Deep Sea Drilling Project. Model 1 results in a ranked optimum sequence that is significant at a lower limit of probability. Model 2 results in both a ranked sequence, and a scaled sequence tied to statistical significance. The ranked solutions are similar in their overall trends, but important differences are apparent. These differences can be attributed to specific assumptions and algorithms explicit for each model, and include the initial evaluation of sampling density for the dataset, the handling of coeval events, and the assumed frequency distribution of an event occurrence in time. An optimum solution for the dataset can be obtained using the ranking approach of Model 1 and the scaling approach of Model 2
Year of Publication: 1984
Research Program: DSDP Deep Sea Drilling Project
Key Words: 12 Stratigraphy, Historical Geology and Paleoecology; Algae; Atlantic Ocean; Autocorrelation; Binomial models; Biostratigraphy; Cenozoic; Correlation; Data processing; Deep Sea Drilling Project; IGCP; Marine sediments; Mathematical models; Mesozoic; Methods; Microfossils; Nannofossils; Plantae; Probability; Sediments; Statistical analysis; Stratigraphy; Thallophytes
Record ID: 1984055509
Copyright Information: GeoRef, Copyright 2019 American Geosciences Institute.

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