A model for longitudinal data sets relating wind-damage probability to biotic and abiotic factors: a Bayesian approach

Kiyoshi Umeki, Marc David Abrams, Keisuke Toyama, Eri Nabeshima

Open source

DOI: 10.5424/fs/2019283-15200
Published: 2019-12-19
Container: Forest Systems
Publisher: Editorial CSIC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.5424/fs/2019283-15200,
  title = {A model for longitudinal data sets relating wind-damage probability to biotic and abiotic factors: a Bayesian approach},
  author = {Kiyoshi Umeki and Marc David Abrams and Keisuke Toyama and Eri Nabeshima},
  year = {2019},
  journal = {Forest Systems},
  doi = {10.5424/fs/2019283-15200},
  url = {https://doi.org/10.5424/fs/2019283-15200}
}

RIS

TY  - JOUR
TI  - A model for longitudinal data sets relating wind-damage probability to biotic and abiotic factors: a Bayesian approach
AU  - Kiyoshi Umeki
AU  - Marc David Abrams
AU  - Keisuke Toyama
AU  - Eri Nabeshima
PY  - 2019
JO  - Forest Systems
DO  - 10.5424/fs/2019283-15200
UR  - https://doi.org/10.5424/fs/2019283-15200
ER  -

APA

Umeki, K., Abrams, M. D., Toyama, K., & Nabeshima, E. (2019). A model for longitudinal data sets relating wind-damage probability to biotic and abiotic factors: a Bayesian approach. Forest Systems. https://doi.org/10.5424/fs/2019283-15200

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crossref · retrieved 2026-09-26T05:19:43.970Z