Characterization of exponential families of lumpable stochastic matrices

Abstract It is known that the set of lumpable Markov chains over a finite state space, with respect to a fixed lumping function, generally does not form an exponential family of stochastic matrices. In this work, we explore efficiently verifiable necessary and sufficient conditions for families of lumpable transition matrices to form exponential families. To this end, we develop a broadly applicable dimension-based method for determining whether a given family of stochastic matrices forms an exponential family.

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Publication Details

Journal
Information Geometry
Published
2026-04-06
DOI
https://doi.org/10.1007/s41884-026-00194-7
Primary Topic
Markov Chains and Monte Carlo Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

Characterization of exponential families of lumpable stochastic matrices

Geoffrey Wolfer, Shun Watanabe
Information Geometry
Markov Chains and Monte Carlo Methods
article

Characterization of exponential families of lumpable stochastic matrices

Geoffrey Wolfer, Shun Watanabe
article en

Abstract

Abstract It is known that the set of lumpable Markov chains over a finite state space, with respect to a fixed lumping function, generally does not form an exponential family of stochastic matrices. In this work, we explore efficiently verifiable necessary and sufficient conditions for families of lumpable transition matrices to form exponential families. To this end, we develop a broadly applicable dimension-based method for determining whether a given family of stochastic matrices forms an exponential family.

Information Geometry
Tokyo University of Agriculture and Technology (JP)
Japan Society for the Promotion of Science, Japan Science and Technology Agency
Openalex Percentile: Top 18%
Markov Chains and Monte Carlo Methods
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