On Fisher information inequalities in the presence of nuisance parameters

Vasant P. Bhapkar, Cidambi Srinivasan

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


The existence of a generalized Fisher information matrix for a vector parameter of interest is established for the case where nuisance parameters are present under general conditions. A matrix inequality is established for the information in an estimating function for the vector parameter of interest. It is shown that this inequality leads to a sharper lower bound for the variance matrix of unbiased estimators, for any set of functionally independent functions of parameters of interest, than the lower bound provided by the Cramér-Rao inequality in terms of the full parameter.

Original languageEnglish
Pages (from-to)593-604
Number of pages12
JournalAnnals of the Institute of Statistical Mathematics
Issue number3
StatePublished - Sep 1994


  • Information matrix
  • estimating functions
  • partial ancillarity
  • partial sufficiency

ASJC Scopus subject areas

  • Statistics and Probability


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