Identifying Markov Chain Models from Time-to-Event Data: An Algebraic Approach

Ovidiu Radulescu, Dima Grigoriev, Matthias Seiss, Maria Douaihy, Mounia Lagha, Edouard Bertrand

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DOI: 10.1007/s11538-024-01385-y
Published: 2024-12-03
Container: Bulletin of Mathematical Biology
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s11538-024-01385-y,
  title = {Identifying Markov Chain Models from Time-to-Event Data: An Algebraic Approach},
  author = {Ovidiu Radulescu and Dima Grigoriev and Matthias Seiss and Maria Douaihy and Mounia Lagha and Edouard Bertrand},
  year = {2024},
  journal = {Bulletin of Mathematical Biology},
  doi = {10.1007/s11538-024-01385-y},
  url = {https://doi.org/10.1007/s11538-024-01385-y}
}

RIS

TY  - JOUR
TI  - Identifying Markov Chain Models from Time-to-Event Data: An Algebraic Approach
AU  - Ovidiu Radulescu
AU  - Dima Grigoriev
AU  - Matthias Seiss
AU  - Maria Douaihy
AU  - Mounia Lagha
AU  - Edouard Bertrand
PY  - 2024
JO  - Bulletin of Mathematical Biology
DO  - 10.1007/s11538-024-01385-y
UR  - https://doi.org/10.1007/s11538-024-01385-y
ER  -

APA

Radulescu, O., Grigoriev, D., Seiss, M., Douaihy, M., Lagha, M., & Bertrand, E. (2024). Identifying Markov Chain Models from Time-to-Event Data: An Algebraic Approach. Bulletin of Mathematical Biology. https://doi.org/10.1007/s11538-024-01385-y

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crossref · retrieved 2026-09-25T02:43:11.347Z