A provenance study of French limestone based on variable selection from compositional profiles

  1. Pizarro, C. 1
  2. González-Sáiz, J.M. 1
  3. Esteban-Díez, I. 1
  4. Sáenz-González, C. 1
  5. Pérez-Del-Notario, N. 1
  6. Rodríguez-Tecedor, S. 1
  1. 1 Universidad de La Rioja

    Universidad de La Rioja

    Logroño, España

    GRID grid.119021.a


ISSN: 0003-813X

Year of publication: 2011

Volume: 53

Issue: 6

Pages: 1099-1118

Type: Article

Export: RIS
DOI: 10.1111/j.1475-4754.2011.00587.x SCOPUS: 2-s2.0-80855138738 WoS: 000296903300002 GOOGLE SCHOLAR


Cited by

  • Scopus Cited by: 0 (03-09-2021)

Journal Citation Reports

  • Year 2011
  • Journal Impact Factor: 1.183
  • Best Quartile: Q3
  • Area: CHEMISTRY, ANALYTICAL Quartile: Q3 Rank in area: 50/73 (Ranking edition: SCIE)
  • Area: GEOSCIENCES, MULTIDISCIPLINARY Quartile: Q3 Rank in area: 93/170 (Ranking edition: SCIE)
  • Area: CHEMISTRY, INORGANIC & NUCLEAR Quartile: Q3 Rank in area: 28/44 (Ranking edition: SCIE)

SCImago Journal Rank

  • Year 2011
  • SJR Journal Impact: 0.873
  • Best Quartile: Q1
  • Area: Archeology Quartile: Q1 Rank in area: 17/226
  • Area: History Quartile: Q1 Rank in area: 22/1011


  • Social Sciences: A
  • Human Sciences: A+


  • Year 2011
  • CiteScore of the Journal : 2.6
  • Area: History Percentile: 98
  • Area: Archeology Percentile: 93


The present study shows how multivariate analysis and variable selection techniques can be used in archaeological provenances studies to improve classification performances. Neutron activation analysis (NAA), in combination with stepwise linear discrimination analysis (SLDA) (capable of simultaneously performing variable selection and classification), was applied to differentiate among limestone samples from different quarries across the north of France based on their compositional fingerprint. A hierarchical classification approach was followed, aimed at progressively assigning limestone samples to more specific sources of origin, from the broadest classification units (French regions) to the narrowest ones (individual quarries). The application of the stepwise variable selection procedure to extract the most discriminating compositional variables prior to each classification development allowed us to obtain a perfect separation between the limestone categories considered at every classification stage (all samples were correctly classified and predicted in all cases). The high-quality results obtained were even more remarkable considering the relatively small number of significant variables selected in each case using the SLDA method. An illustrative example was provided in order to demonstrate that the classification strategy proposed can actually allocate an unknown sculpture to a particular quarry of origin. © University of Oxford, 2011.