A Bayesian lower bound for parameters with bounded support priors

Raksha Ramakrishna, Anna Scaglione

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we derive a Bayesian lower bound on the estimation of a scalar parameter whose prior distribution is assumed to have a bounded support. For such truncated prior distributions it is well known that the Bayesian Cramer-Rao bound (BCRB) does not hold. We also analyze the tightness of this bound for maximum a-posteriori estimators (MAP) in the case of conditionally Gaussian observations and highlight some interesting properties. Numerical results illustrate the tightness of this bound. We also study the utility of this bound in an application to a real-world system of fault detection in solar panels.

Original languageEnglish (US)
Title of host publication2020 54th Annual Conference on Information Sciences and Systems, CISS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728140841
DOIs
StatePublished - Mar 2020
Event54th Annual Conference on Information Sciences and Systems, CISS 2020 - Princeton, United States
Duration: Mar 18 2020Mar 20 2020

Publication series

Name2020 54th Annual Conference on Information Sciences and Systems, CISS 2020

Conference

Conference54th Annual Conference on Information Sciences and Systems, CISS 2020
CountryUnited States
CityPrinceton
Period3/18/203/20/20

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Artificial Intelligence

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    Ramakrishna, R., & Scaglione, A. (2020). A Bayesian lower bound for parameters with bounded support priors. In 2020 54th Annual Conference on Information Sciences and Systems, CISS 2020 [9086249] (2020 54th Annual Conference on Information Sciences and Systems, CISS 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISS48834.2020.1570624061