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Bayesian Inference from Symplectic Geometric Viewpoint

DOI: 10.4236/apm.2019.910039, PP. 827-831

Keywords: Bayesian Inference, Hamiltonian, Symplectic, Canonical Transformation

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Abstract:

The purpose of this article is to formulate Bayesian updating from dynamical viewpoint. We prove that Bayesian updating for population mean vectors of multivariate normal distributions can be expressed as an affine symplectic transformation on a phase space with the canonical symplectic structure.

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