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Information Bounds and Nonparametric Maximum Likelihood Estimation

This book contains the lecture notes for a DMV course presented by the authors at Gunzburg, Germany, in September, 1990. In the course we sketched the theory of information bounds for non parametric and semiparametric models, and developed the theory of non parametric maximum likelihood estimation i...

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Bibliographic Details
Main Authors: Groeneboom, P., Wellner, J.A. (Author)
Format: eBook
Language:English
Published: Basel Birkhäuser Basel 1992, 1992
Edition:1st ed. 1992
Series:Oberwolfach Seminars
Subjects:
Applied Mathematics
Engineering Mathematics
Applications Of Mathematics
Probability Theory And Stochastic Processes
Probabilities
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • I. Information Bounds
  • 1 Models, scores, and tangent spaces
  • 2 Convolution and asymptotic minimax theorems
  • 3 Van der Vaart’s Differentiability Theorem
  • II. Nonparametric Maximum Likelihood Estimation
  • 1 The interval censoring problem
  • 2 The deconvolution problem
  • 3 Algorithms
  • 4 Consistency
  • 5 Distribution theory
  • References

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