Markov-bridge representation of ergodic large-deviation principles

Fuente: arXiv
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Main Author: Renger, D. R. Michiel
Format: Preprint
Published: 2024
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author Renger, D. R. Michiel
author_facet Renger, D. R. Michiel
contents We revisit classic ergodic large-deviation principles: for the occupation measure (Donsker-Varadhan), and for the empirical flux. We show that these problems can be embedded into a more general, discrete-time framework. A conditioning and mixing argument then yields alternative expressions for these well-known rate functionals, formulated in terms of Markov bridges.
format Preprint
id arxiv_https___arxiv_org_abs_2407_00216
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Markov-bridge representation of ergodic large-deviation principles
Renger, D. R. Michiel
Probability
60F10 60J10 60J27 60F10 60J10 60J27 60F10 60J10 60J27 60F10 60J10 60J27 60F10 60J10 60J27 60F10, 60J10, 60J27
We revisit classic ergodic large-deviation principles: for the occupation measure (Donsker-Varadhan), and for the empirical flux. We show that these problems can be embedded into a more general, discrete-time framework. A conditioning and mixing argument then yields alternative expressions for these well-known rate functionals, formulated in terms of Markov bridges.
title Markov-bridge representation of ergodic large-deviation principles
topic Probability
60F10 60J10 60J27 60F10 60J10 60J27 60F10 60J10 60J27 60F10 60J10 60J27 60F10 60J10 60J27 60F10, 60J10, 60J27
url https://arxiv.org/abs/2407.00216