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

Radulescu O, Grigoriev D, Seiss M, Douaihy M, Lagha M, Bertrand E

DOI: 10.1007/s11538-024-01385-y
Published: 2024 Dec 3
Container: Bulletin of mathematical biology
Publisher: Not recorded
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 = {Radulescu O and Grigoriev D and Seiss M and Douaihy M and Lagha M and Bertrand E},
  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  - Radulescu O
AU  - Grigoriev D
AU  - Seiss M
AU  - Douaihy M
AU  - Lagha M
AU  - Bertrand E
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

O, R., D, G., M, S., M, D., M, L., & E, B. (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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pubmed · retrieved 2026-11-10T10:04:02.122Z