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Maximum probability estimators with a general loss function

  • L. Weiss
  • J. Wolfowitz
Conference paper
Part of the Lecture Notes in Mathematics book series (LNM, volume 89)

Keywords

Loss Function Maximum Likelihood Estimator Classical Maximum Regular Case Borel Measurable Function 
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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References

  1. [1]
    L. Weiss and J. Wolfowitz—“Maximum probability estimators” Ann. Inst. Stat. Math. 19, No. 2 (1967), 193–206.MathSciNetCrossRefzbMATHGoogle Scholar
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    L. Weiss and J. Wolfowitz—“Generalized maximum likelihood estimators” Teoriya Vyeroyatnostey, 11, No. 1 (1966), 68–93.MathSciNetzbMATHGoogle Scholar
  3. [3]
    J. Wolfowitz—“Asymptotic efficiency of the maximum likelihood estimator” Teoriya Vyeroyatnostey, 10, No. 2 (1965), 267–281.MathSciNetzbMATHGoogle Scholar
  4. [4]
    A. Wald—“Note on the consistency of the maximum likelihood estimate” Ann. Math. Stat., 20, No. 4 (1949), 595–600.MathSciNetCrossRefzbMATHGoogle Scholar
  5. [5]
    H. Cramér—“Mathematical methods of statistics” Princeton University Press, 1946, Princeton, N. J.Google Scholar
  6. [6]
    S. Kaufman—“Asymptotic efficiency of the maximum likelihood estimator” Ann. Inst. Stat. Math. 18, No. 2 (1966), 155–178.MathSciNetCrossRefzbMATHGoogle Scholar
  7. [7]
    A. Wald “Asymptotic minimax solutions of sequential point estimation problems” Proc. Second Berkeley Symposium on Mathematical Statistics and Probability, 1950. Berkeley and Los Angeles, University of California Press, 1951.zbMATHGoogle Scholar

Copyright information

© Springer-Verlag 1969

Authors and Affiliations

  • L. Weiss
    • 1
  • J. Wolfowitz
    • 1
  1. 1.Cornell UniversityIthaca

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