Nonparametric Functional Methods: New Tools for Chemometric Analysis

Frédéric Ferraty, Aldo Goia and Philippe Vieu

Chapter 13 in Statistical Methods for Biostatistics and Related Fields, 2007, pp 245-264 from Springer

Abstract: 13.5 Concluding Comments In this contribution, we have shown how spectrometric data can be succesfully analysed by considering them as curve data and by using the recent nonparametric methodology for curve data. However, note that all the statistical backgrounds are presented in a general way (and not only for spectrometric data). Similarly, the XploRe quantlets that we provided can be directly used in any other applied setting involving curve data. For reason of shortness, and because it was not the purpose here, we only presented the results given by the nonparametric functional methodology without discussing any comparison with alternative methods (but relevant references on these points are given all along the contribution). Also for shortness reasons, we just presented two statistical problems (namely regression from curve data and curves discrimination) among the several problems that can be treated by nonparametric functional methods (on this point also, our contribution contains several references about other problems that could be attacked similarly). These two problems have been chosen by us for two reasons: first, these issues are highly relevant to many applied studies involving curve analysis and second, their theoretical and practical importance led to emergence of different computer automated procedures.

Keywords: Curve Data; Spectrometric Data; Discrimination Problem; Learning Sample; Chemometric Analysis (search for similar items in EconPapers)
Date: 2007
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
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: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-32691-5_13

Ordering information: This item can be ordered from
http://www.springer.com/9783540326915

DOI: 10.1007/978-3-540-32691-5_13

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().