Some Inequalities Between Pairs of Marginal and Joint Bayesian Lower Bounds

Bacharach L., Chaumette E., Fritsche C., ORGUNER U.

22nd International Conference on Information Fusion (FUSION), Ottawa, Canada, 2 - 05 July 2019 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • City: Ottawa
  • Country: Canada
  • Middle East Technical University Affiliated: Yes


In this paper, tightness relations (or inequalities) between Bayesian lower bounds (BLBs) on the mean-squared-error are derived which result from the marginalization of a joint probability density function (pdf) depending on both parameters of interest and extraneous or nuisance parameters. In particular, it is shown that for a large class of BLBs, the BLB derived from the marginal pdf is at least as tight as the corresponding BLB derived from the joint pdf. A Bayesian linear regression example is used to illustrate the tightness relations.