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Inference for partially observed Riemannian Ornstein–Uhlenbeck diffusions of covariance matrices

Bui, Mai Ngoc; Pokern, Yvo; Dellaportas, Petros; (2023) Inference for partially observed Riemannian Ornstein–Uhlenbeck diffusions of covariance matrices. Bernoulli: a journal of mathematical statistics and probability , 29 (4) pp. 2961-2986. 10.3150/22-BEJ1570. Green open access

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Abstract

We construct a generalization of the Ornstein–Uhlenbeck processes on the cone of covariance matrices endowed with the Log-Euclidean and the Affine-Invariant metrics. Our development exploits the Riemannian geometric structure of symmetric positive definite matrices viewed as a differential manifold. We then provide Bayesian inference for discretely observed diffusion processes of covariance matrices based on an MCMC algorithm built with the help of a novel diffusion bridge sampler accounting for the geometric structure. Our proposed algorithm is illustrated with a real data financial application.

Type: Article
Title: Inference for partially observed Riemannian Ornstein–Uhlenbeck diffusions of covariance matrices
Open access status: An open access version is available from UCL Discovery
DOI: 10.3150/22-BEJ1570
Publisher version: https://doi.org/10.3150/22-BEJ1570
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Affine-Invariant metric; Log-Euclidean metric; Ornstein–Uhlenbeck process; Riemannian manifold; Partially observed diffusion
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Applied Health Research
URI: https://discovery.ucl.ac.uk/id/eprint/10161285
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