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Lecture: Empirical Processes and Consistency of Z-Estimators

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

Abstract

In this lecture and the next lecture we discuss empirical processes. Our main focus is the application of empirical processes to the derivation of asymptotic properties of estimators in semiparametric models. In this first lecture we discuss entropy numbers, Glivenko—Cantelli classes and their application to proving consistency of M- and Z-estimators.

Keywords

  • Maximum Likelihood Estimator
  • Dominate Convergence Theorem
  • Empirical Process
  • Envelope Function
  • Semiparametric Model

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© 2002 Springer-Verlag Berlin Heidelberg

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(2002). Lecture: Empirical Processes and Consistency of Z-Estimators. 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_14

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  • DOI: https://doi.org/10.1007/3-540-47944-9_14

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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