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Title: Holocene Paleointensity of the Island of Hawai `i From Glassy Volcanics: HOLOCENE HAWAIIAN PALEOINTENSITY
NSF-PAR ID:
10075329
Author(s) / Creator(s):
 ;  ;  ;  ;  
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Geochemistry, Geophysics, Geosystems
Volume:
19
Issue:
9
ISSN:
1525-2027
Page Range / eLocation ID:
p. 3224-3245
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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  2. Abstract

    The assumptions of paleointensity experiments are violated in many natural and archeological materials, leading to Arai plots which do not appear linear and yield inaccurate paleointensity estimates, leading to bias in the result. Recently, paleomagnetists have adopted sets of “selection criteria” that exclude specimens with nonlinear Arai plots from the analysis, but there is little consensus in the paleomagnetic community on which set to use. In this study, we present a statistical method we call Bias Corrected Estimation of Paleointensity (BiCEP), which assumes that the paleointensity recorded by each specimen is biased away from a true answer by an amount that is dependent a single metric of nonlinearity (the curvature parameter) on the Arai plot. We can use this empirical relationship to estimate the recorded paleointensity for a specimen where, that is, a perfectly straight line. We apply the BiCEP method to a collection of 30 sites for which the true value of the original field is well constrained. Our method returns accurate estimates of paleointensity, with similar levels of accuracy and precision to restrictive sets of paleointensity criteria, but accepting as many sites as permissive criteria. The BiCEP method has a significant advantage over using these selection criteria because it achieves these accurate results without excluding large numbers of specimens from the analysis. It yields accurate, albeit imprecise estimates from sites whose specimens all fail traditional criteria. BiCEP combines the accuracy of the strictest selection criteria with the low failure rates of the less reliable “loose” criteria.

     
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