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Multiblock latent root regression. Application to epidemiological data

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Abstract

Several papers have already stressed the interest of latent root regression and its similarities to partial least squares regression. A new formulation of this method which makes it even simpler than the original method to set up a prediction model is discussed. Furthermore, it is shown how this method can be extended not only to the case where it is desired to predict several response variables from a set of predictors but also to the multiblock setting where the aim is to predict one or several data sets from several other data sets. The interest of the method is illustrated on the basis of a data set pertaining to epidemiology.

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References

  • Bertrand D, Qannari EM, Vigneau E (2001) Latent root regression analysis: an alternative method to PLS. Chemom Intell Lab Sys 58:227–234

    Article  Google Scholar 

  • Draper NR, Smith H (1981) Applied regression analysis. Wiley, New York, p 709

    MATH  Google Scholar 

  • Lafosse R, Hanafi M (1997) Concordance d’un tableau avec K tableaux : définition de K + 1uples synthétiques. Revue de statistique appliquée XLV:111–126

    Google Scholar 

  • Rao CR (1964) The use and interpretation of principal component analysis in applied research. Sankhya A 26:329–358

    MATH  Google Scholar 

  • Stone M (1974) Cross-validatory choice and assessment of statistical predictions. J R Stat Soc 36:111–147

    MATH  Google Scholar 

  • Tenenhaus M, Hanafi M (2005) Use of PLS path modelling for the analysis of multiblock data. In: Proceedings of 4th international symposium on PLS and related methods, Barcelona, September 7th-9th

  • Van Den Berg F (2001) Multi-block toolbox for Matlab (http://www.models.kvl.dk/source/ MBToolbox/). Royal Veterinary and Agricultural University, Department of Food Science, Copenhagen

  • Vivien M (1999) Nouvelles approches en analyse multi-tableaux. Report, University of Montpellier II

  • Vivien M (2002) Approches PLS linéaires et non-linéaires pour la modélisation de multi-tableaux : théorie et applications. Thesis, University of Montpellier I

  • Webster T, Gunst RF, Mason RL (1974) Latent root regression analysis. Technometrics 16:513–522

    Article  MATH  MathSciNet  Google Scholar 

  • Westerhuis JA, Kourti T, MacGregor JF (1998) Analysis of multiblock and hierarchical PCA and PLS model. J Chemom 12:301–321

    Article  Google Scholar 

  • Wold H (1982) Soft modelling: the basic design and some extensions. In: Jreskog KG, Wold H (eds) System under indirect observation. Part 2. North-Holland, Amsterdam, pp 1–54

    Google Scholar 

  • Wold S, Martens H, Wold H (1983) The multivariate calibration problem in chemistry solved by the PLS method. In: Ruhe A, Kastrom B (eds) Proceedings of conference in matrix pencils, 1982. Lecture notes in mathematics, Springer, Heidelberg, pp 286–293

  • Wold S, Kettaneh N, Tjessem K (1996) Hierarchical multiblock PLS and PC models for easier model interpretation and as an alternative to variable selection. J chemom 10:463–482

    Article  Google Scholar 

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Authors and Affiliations

  1. Département d’épidémiologie animale, Les Croix, AFSSA, BP53, 22440, Ploufragan, France

    Stéphanie Bougeard

  2. ENITIAA-INRA, Unité de Sensométrie et Chimiométrie, Rue de la Géraudière, BP 82225, 44322, Nantes Cedex, France

    Mohamed Hanafi & El Mostafa Qannari

Authors
  1. Stéphanie Bougeard
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  2. Mohamed Hanafi
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  3. El Mostafa Qannari
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Correspondence to Stéphanie Bougeard.

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Bougeard, S., Hanafi, M. & Qannari, E.M. Multiblock latent root regression. Application to epidemiological data. Computational Statistics 22, 209–222 (2007). https://doi.org/10.1007/s00180-007-0036-1

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  • DOI: https://doi.org/10.1007/s00180-007-0036-1

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