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Preliminary Test Estimation for Multi-Sample Principal Components

Author

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  • Davy Paindaveine
  • Rondrotiana J Rasoafaraniaina
  • Thomas Verdebout

Abstract

In this paper, we consider point estimation in a multi-sample principal components setup, in a situation where it is suspected that the hypothesis of common principal components (CPC) holds. We propose preliminary test estimators of the various principal eigenvectors. We derive their asymptotic distributions (i) under the CPC hypothesis, (ii) under sequences of hypotheses that are contiguous to the CPC hypothesis, and (iii) away from the CPC hypothesis. We conduct a Monte-Carlo study that shows that the proposed estimators perform well, particularly so in the Gaussian case.

Suggested Citation

  • Davy Paindaveine & Rondrotiana J Rasoafaraniaina & Thomas Verdebout, 2016. "Preliminary Test Estimation for Multi-Sample Principal Components," Working Papers ECARES ECARES 2016-39, ULB -- Universite Libre de Bruxelles.
    • Handle: RePEc:eca:wpaper:2013/240546
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    Cited by:

    1. Shastitko. Andrey (Шаститко, Андрей) & Komkova, Anastasia Andreevna (Комкова, Анастасия Андреевна) & Kurdin, Alexander (Курдин, Александр) & Shastitko, Anastasia (Шаститко, Анастасия), 2016. "Competition Policy and Incentives for Innovation [Конкурентная Политика И Стимулы К Инновационной Деятельности]," Working Papers 1447, Russian Presidential Academy of National Economy and Public Administration.

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    Keywords

    preliminary test estimation; common principal components;

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