A Geometric Reduction Approach for Identity Testing of Reversible Markov Chains
Not on the map. Why?
Abstract (arXiv)
We consider the problem of testing the identity of a reversible Markov chain against a reference from a single trajectory of observations. Employing the recently introduced notion of a lumping-congruent Markov embedding, we show that, at least in a mildly restricted setting, testing identity to a reversible chain reduces to testing to a symmetric chain over a larger state space and recover state-of-the-art sample complexity for the problem.
Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 3 of its 15 references that are in the map. First posted on arXiv 16 Feb 2023.
Builds on
3 of 15 references.
References · 3
- 2019Minimax Testing of Identity to a Reference Ergodic Markov Chaincited by 7
- 2014ℓp Testing and Learning of Discrete Distributionscited by 6
- 2021Identity testing of reversible Markov chainscited by 4
Built on by
Not cited yet.