A general class of lower bounds in parameter estimation

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


A general class of Bayesian lower bounds on moments of the error in parameter estimation is formulated, and it is shown that the Cramer-Rao, the Bhattacharyya, the Bobrovsky-Zakai, and the Weiss-Weinstein lower bounds are special cases in the class. The bounds can be applied to the estimation of vector parameters and any given function of the parameters.

Original languageEnglish
Title of host publicationBayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
PublisherWiley-IEEE Press
Number of pages4
ISBN (Electronic)9780470544198
ISBN (Print)0470120959, 9780470120958
StatePublished - 1 Jan 2007


  • Bayesian methods
  • Covariance matrix
  • Estimation
  • Linear matrix inequalities
  • Matrices
  • Parameter estimation
  • Sea measurements


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