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Parameter Estimation for an i.i.d. Model

  • Wolfgang Karl Härdle
  • Vladimir Spokoiny
  • Vladimir Panov
  • Weining Wang
Chapter
Part of the Springer Texts in Statistics book series (STS)

Exercise 2.1 (Glivenko-Cantelli theorem).

Let F be the distribution function of a random variable X and let \(\{X_{i}\}_{i=1}^{n}\)

References

  1. Shao, J. (2005). Mathematical statistics: Exercises and solutions. New York: SpringerGoogle Scholar
  2. Spokoiny, V., & Dickhaus, T. (2014). Basics of modern parametric statistics. Berlin: Springer.Google Scholar
  3. Suhov, Y., & Kelbert, M. (2005). Probability and statistics by example, 1 basic probability and statistics. New York: Cambridge University Press.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Wolfgang Karl Härdle
    • 1
  • Vladimir Spokoiny
    • 2
  • Vladimir Panov
    • 3
  • Weining Wang
    • 1
  1. 1.L.v.Bortkiewicz Chair of Statistics, C.A.S.E. Centre f. Appl. Stat. and Econ.Humboldt-Universität zu BerlinBerlinGermany
  2. 2.Weirstrass Institute for Applied Analysis and Stochastics (WIAS)BerlinGermany
  3. 3.Universität Duisburg-EssenEssenGermany

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