Seriation by constrained correspondence analysis: A simulation study

Michel van de Velden, Patrick Groenen () and Jeroen Poblome

Computational Statistics & Data Analysis, 2009, vol. 53, issue 8, pages 3129-3138

Abstract: One of the many areas in which correspondence analysis (CA) is an effective method, concerns seriation problems.For example, CA is a well-known technique for the seriation of archaeological assemblages. A problem with the CA seriation solution, however, is that only a relative ordering of the assemblages is obtained. To improve the usual CA solution, a constrained CA approach that incorporates additional information in the form of equality and inequality constraints concerning the time points of the assemblages may be considered. Using such constraints, explicit dates can be assigned to the seriation solution. The set of constraints that can be used in CA by introducing interval constraints is extended. That is, constraints that put the CAsolution within a specific time frame. Moreover, the quality of the constrained CA solution is studied in a simulation study. In particular, by means of the simulation study we are able to assess how well ordinary, and constrained CA can recover the true time order. Furthermore, for the constrained approach, it is shown that the true dates are retrieved satisfactory. The simulation study is set up in such a way that it mimics the data of a series of ceramic assemblages consisting of the locally produced tableware from Sagalassos (SW Turkey). It is found that the dating of the assemblages on the basis of constraints appears to work quite well.

Date: 2009

Downloads: (external link)
http://www.sciencedirect.com/science/article/B6V8V ... 7b532a76e68c3000db72
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Seriation by constrained correspondence analysis: a simulation study (2007)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:eee:csdana:v:53:y:2009:i:8:p:3129-3138

Access Statistics for this article

Computational Statistics & Data Analysis is edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Series data maintained by Heidi Boesdal ().