Performance Bounds and Uncertainty Quantification

David Ramírez, Ignacio Santamaría and Louis Scharf
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David Ramírez: Universidad Carlos III de Madrid
Ignacio Santamaría: Universidad de Cantabria
Louis Scharf: Colorado State University

Chapter 10 in Coherence, 2022, pp 297-316 from Springer

Abstract: Abstract This chapter begins with the Hilbert space geometry of quadratic performance bounds and then specializes these results to the Euclidean geometry of the Cramér-Rao bound for parameters that are carried in the mean value or the covariance matrix of a MVN model. Coherence arises naturally. A concluding section on information geometry ties the Cramér-Rao bound on error covariance to the resolvability of the underlying probability distribution from which measurements are drawn.

Keywords: Cramér-Rao bound; Information geometry; Fisher score; Fisher information; Efficiency (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-13331-2_10

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DOI: 10.1007/978-3-031-13331-2_10

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