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Asymptotic Properties of M, ML, and Maximum A Posteriori Estimators

  • Luc Pronzato
  • Andrej Pázman
Chapter
Part of the Lecture Notes in Statistics book series (LNS, volume 212)

Abstract

We consider the regression model (3.2) where the errors \(\varepsilon _{i}\) are independently distributed, \(\varepsilon _{i}\) having the p.d.f.\(\bar{\varphi }_{x_{i}}(\cdot )\).

Keywords

Independent Random Variable Exponential Family Fisher Information Matrix Finite Measure Asymptotic Efficiency 
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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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Luc Pronzato
    • 1
  • Andrej Pázman
    • 2
  1. 1.French National Center for Scientific Research (CNRS)University of NiceSophia AntipolisFrance
  2. 2.Department of Applied Mathematics and StatisticsComenius UniversityBratislavaSlovakia

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