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Improving Cramér-Rao Bound With Multivariate Parameters: An Extrinsic Geometry Perspective

Published: September 23, 2025 | arXiv ID: 2509.18978v1

By: Sunder Ram Krishnan

Potential Business Impact:

Improves how well we can measure things precisely.

Business Areas:
A/B Testing Data and Analytics

We derive a vector generalization of the square root embedding-based curvature-corrected Cram\'er--Rao bound (CRB) previously considered by the same author in \cite{srk} with scalar parameters. A \emph{directional} curvature correction is established first, and sufficient conditions for a conservative matrix-level CRB refinement are formulated using a simple semidefinite program. The directional correction theorem is rigorously illustrated with a Gaussian example.

Page Count
15 pages

Category
Mathematics:
Statistics Theory