Estimating Equations and Maximum Likelihood

  • Robert W. Keener
Part of the Springer Texts in Statistics book series (STS)


Many estimators in statistics are specified implicitly as solutions to equations or as values maximizing some function. In this chapter we study why these methods work and learn ways to approximate distributions. Although we focus on methods for i.i.d. observations, many of the ideas can be extended. Results for stationary time series are sketched in Section 9.9.


Random Vector Central Limit Theorem Initial Guess Maximum Likelihood Estimator Random Function 
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Copyright information

© Springer New York 2009

Authors and Affiliations

  • Robert W. Keener
    • 1
  1. 1.Department of StatisticsUniversity of MichiganAnn ArborUSA

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