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

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


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


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