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Lecture: Rates of Convergence

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Part of the Lecture Notes in Mathematics book series (LNMECOLE,volume 1781)

Abstract

In this lecture we apply maximal inequalities for empirical processes to obtain rates of convergence of minimum contrast estimators, in particular in semiparametric models. These rates are of interest by themselves, but will also be needed to prove the asymptotic normality of semiparametric likelihood estimators in certain models.

Keywords

  • Maximum Likelihood Estimator
  • Asymptotic Normality
  • Nuisance Parameter
  • Empirical Process
  • Maximal Inequality

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© 2002 Springer-Verlag Berlin Heidelberg

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(2002). Lecture: Rates of Convergence. In: Bernard, P. (eds) Lectures on Probability Theory and Statistics. Lecture Notes in Mathematics, vol 1781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47944-9_17

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  • DOI: https://doi.org/10.1007/3-540-47944-9_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43736-9

  • Online ISBN: 978-3-540-47944-4

  • eBook Packages: Springer Book Archive