Some Inequalities Between Pairs of Marginal and Joint Bayesian Lower Bounds

2019-01-01
Bacharach, Lucien
Chaumette, Eric
Fritsche, Carsten
Orguner, Umut
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.

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Citation Formats
L. Bacharach, E. Chaumette, C. Fritsche, and U. Orguner, “Some Inequalities Between Pairs of Marginal and Joint Bayesian Lower Bounds,” 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53913.