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A Variation of the F-Test for Determining Statistical Relevance of Particular Parameters in EXAFS Fits
AIP conference proceedings · 2007 · Vol. 882 · pp. 129–131
L. Downward✉(University of California, Santa Cruz)Corwin H. Booth(Lawrence Berkeley National Laboratory)Wayne W. Lukens(Lawrence Berkeley National Laboratory)F. Bridges(University of California, Santa Cruz)
Abstract
A general problem when fitting EXAFS data is determining whether particular parameters are statistically significant. The F-test is an excellent way of determining relevancy in EXAFS because it only relies on the ratio of the fit residual of two possible models, and therefore the data errors approximately cancel. Although this test is widely used in crystallography (there, it is often called a “Hamilton test”) and has been properly applied to EXAFS data in the past, it is very rarely applied
Thermal Expansion and Ionic ConductivityX-ray Spectroscopy and Fluorescence AnalysisAdvanced NMR Techniques and ApplicationsRelevance (law)Variation (astronomy)StatisticsComputer scienceStatistical physicsEconometricsMathematicsPhysicsPolitical science
Funding
- National Science Foundation
- U.S. Department of Energy
- Office of Science
- Division of Materials Research
- Basic Energy Sciences
Citations
144
FWCI
1.11
field-weighted impact
References
1
Percentile
76%
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Citations per year
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