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Estimation of significance levels and confidence intervals for first-order reversal curve distributions

Heslop, David; Roberts, Andrew

Description

First-order reversal curve (FORC) distributions provide a means with which to describe a magnetic mineral assemblage in terms of coercivities and interaction fields. In recent years the use of experimentally derived FORC distributions has increased dramatically and they are being placed in an increasingly quantitative interpretational framework. An outstanding issue for calculation and interpretation of FORC data sets is the statistical significance that can be assigned to structures in...[Show more]

dc.contributor.authorHeslop, David
dc.contributor.authorRoberts, Andrew
dc.date.accessioned2015-12-10T23:13:50Z
dc.identifier.issn1525-2027
dc.identifier.urihttp://hdl.handle.net/1885/64604
dc.description.abstractFirst-order reversal curve (FORC) distributions provide a means with which to describe a magnetic mineral assemblage in terms of coercivities and interaction fields. In recent years the use of experimentally derived FORC distributions has increased dramatically and they are being placed in an increasingly quantitative interpretational framework. An outstanding issue for calculation and interpretation of FORC data sets is the statistical significance that can be assigned to structures in experimentally determined distributions. Without this knowledge, the selection and characterization of structures that can be deemed interpretable within a FORC distribution is a subjective process. We demonstrate how FORC processing algorithms can be adapted to provide a measure of statistical significance and a confidence interval for each point in a FORC distribution. This information can guide measurement protocols and provides a more quantitative framework for interpretation of FORC distributions.
dc.publisherAmerican Geophysical Union
dc.rightsAuthor/s retain copyright
dc.sourceGeochemistry, Geophysics, Geosystems. G3
dc.subjectKeywords: Characterization of structure; Coercivities; Confidence interval; Data sets; First-order reversal curves; Interaction fields; Magnetic minerals; Measurement protocol; Processing algorithms; Significance level; Statistical significance; Magnetic hysteresis Confidence interval; First-order reversal curves; Significance level
dc.titleEstimation of significance levels and confidence intervals for first-order reversal curve distributions
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume13
dc.date.issued2012
local.identifier.absfor040400 - GEOPHYSICS
local.identifier.ariespublicationf5625xPUB967
local.type.statusPublished Version
local.contributor.affiliationHeslop, David, College of Physical and Mathematical Sciences, ANU
local.contributor.affiliationRoberts, Andrew, College of Physical and Mathematical Sciences, ANU
local.bibliographicCitation.issue12
local.identifier.doi10.1029/2012GC004115
dc.date.updated2016-02-24T09:46:03Z
local.identifier.scopusID2-s2.0-84861360642
local.identifier.thomsonID000304259000002
dcterms.accessRightsOpen Access
CollectionsANU Research Publications

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