Application of the parametric bootstrap method to determine statistical errors in quantitative X-ray microanalysis of thin films (Articolo in rivista)

Type
Label
  • Application of the parametric bootstrap method to determine statistical errors in quantitative X-ray microanalysis of thin films (Articolo in rivista) (literal)
Anno
  • 2007-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1111/j.1365-2818.2007.01817.x (literal)
Alternative label
  • Armigliato A, Balboni R, Rosa R (2007)
    Application of the parametric bootstrap method to determine statistical errors in quantitative X-ray microanalysis of thin films
    in Journal of microscopy (Print); Blackwell Publishing, Oxford (Regno Unito)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Armigliato A, Balboni R, Rosa R (literal)
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  • 1 (literal)
Pagina fine
  • 10 (literal)
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  • 228 (literal)
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  • 10 (literal)
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  • 1 (literal)
Note
  • Scopu (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR-IMM, Sez Bologna, I-40129 Bologna, Italy; Univ Bologna, Dipartimento Sci & Stat, I-40126 Bologna, Italy (literal)
Titolo
  • Application of the parametric bootstrap method to determine statistical errors in quantitative X-ray microanalysis of thin films (literal)
Abstract
  • We applied the parametric bootstrap to the X-ray microanalysis of Si-Ge binary alloys, in order to assess the dependence of the Ge concentrations and the local film thickness, obtained by using previously described Monte Carlo methods, on the precision of the measured intensities. We show how it is possible by this method to determine the statistical errors associated with the quantitative analysis performed in sample regions of different composition and thickness, but by conducting only one measurement. We recommend the use of the bootstrap for a broad range of applications for quantitative microanalysis to estimate the precision of the final results and to compare the performances of different methods to each other. Finally, we exploited a test based on bootstrap confidence intervals to ascertain if, for given X-ray intensities, different values of the estimated composition in two points of the sample are indicative of an actual lack of homogeneity. (literal)
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