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Data Analysis in Astronomy III pp 31–38Cite as

Stability in Factor Analyses with Respect to Small Perturbations of the Data and to Departure from Gaussian Law of the Variables

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Part of the book series: Ettore Majorana International Science Series ((EMISS,volume 40))

Abstract

In this paper, we consider the problem of approximations by sampling in the case of the principal component factor analysis. In a first part we recall the asymptotic results of Anderson, Arconte, Davis, Dauxois, Pousse and Romain about the distribution of the proper values of the operators. In a second step, we recall the principle of two non-parametric processes, namely jackknife and bootstrap. In a last stage, we compare the robustness of the asymptotic results mentioned earlier with the results obtained through non parametric processes by means of simulation and drawing of random samples in a given population.

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References

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Author information

Authors and Affiliations

  1. IUT, Univ. Paris X, 1 chemin Desvallières, F-92410, Ville d’Avray, France

    Mireille Ludivine Bougeard

  2. Observatoire Paris, UA 1125 CNRS, F-75014, Paris, France

    Mireille Ludivine Bougeard

Authors
  1. Mireille Ludivine Bougeard
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Editor information

Editors and Affiliations

  1. University of Palermo and Institute of Cosmic Physics and Informatics/CNR, Palermo, Italy

    V. Di Gesù , L. Scarsi  & M. C. Maccarone ,  & 

  2. European Southern Observatory, Garching/Munich, Federal Republic of Germany

    P. Crane

  3. Stanford University, Stanford, California, USA

    J. H. Friedman

  4. University of Rome “La Sapienza”, Rome, Italy

    S. Levialdi

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© 1989 Plenum Press, New York

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Bougeard, M.L. (1989). Stability in Factor Analyses with Respect to Small Perturbations of the Data and to Departure from Gaussian Law of the Variables. In: Di Gesù, V., Scarsi, L., Crane, P., Friedman, J.H., Levialdi, S., Maccarone, M.C. (eds) Data Analysis in Astronomy III. Ettore Majorana International Science Series, vol 40. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-5646-2_3

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  • DOI: https://doi.org/10.1007/978-1-4684-5646-2_3

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4684-5648-6

  • Online ISBN: 978-1-4684-5646-2

  • eBook Packages: Springer Book Archive

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