The embedding problem for Markov matrices

Characterizing whether a Markov process of discrete random variables has a homogeneous continuous-time realization is a hard problem. In practice, this problem reduces to deciding when a given Markov matrix can be written as the exponential of some rate matrix (a Markov generator). This is an old qu...

Descripción completa

Detalles Bibliográficos
Autores: Casanellas i Rius, Marta|||0000-0002-1724-8358, Fernández-Sánchez, Jesus|||0000-0002-7062-8042, Roca-Lacostena, Jordi|||0000-0003-1651-9504
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:271770
Acceso en línea:https://ddd.uab.cat/record/271770
https://dx.doi.org/urn:doi:10.5565/PUBLMAT6712308
Access Level:acceso abierto
Palabra clave:Markov matrix
Markov generator
Embedding problem
Rate identifiability
Descripción
Sumario:Characterizing whether a Markov process of discrete random variables has a homogeneous continuous-time realization is a hard problem. In practice, this problem reduces to deciding when a given Markov matrix can be written as the exponential of some rate matrix (a Markov generator). This is an old question known in the literature as the embedding problem [11], which has been solved only for matrices of size 2 × 2 or 3 × 3. In this paper, we address this problem and related questions and obtain results along two different lines. First, for matrices of any size, we give a bound on the number of Markov generators in terms of the spectrum of the Markov matrix. Based on this, we establish a criterion for deciding whether a generic (distinct eigenvalues) Markov matrix is embeddable and propose an algorithm that lists all its Markov generators. Then, motivated and inspired by recent results on substitution models of DNA, we focus on the 4 × 4 case and completely solve the embedding problem for any Markov matrix. The solution in this case is more concise as the embeddability is given in terms of a single condition.