Recursive Bayesian computation facilitates adaptive optimal design in ecological studies

Clinton B. Leach, Perry J. Williams, Joseph M. Eisaguirre, Jamie N. Womble, Michael R. Bower, Mevin B. Hooten

Open source

DOI: 10.1002/ecy.3573
Published: 2021-11-24
Container: Ecology
Publisher: Wiley
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1002/ecy.3573,
  title = {Recursive Bayesian computation facilitates adaptive optimal design in ecological studies},
  author = {Clinton B. Leach and Perry J. Williams and Joseph M. Eisaguirre and Jamie N. Womble and Michael R. Bower and Mevin B. Hooten},
  year = {2021},
  journal = {Ecology},
  doi = {10.1002/ecy.3573},
  url = {https://doi.org/10.1002/ecy.3573}
}

RIS

TY  - JOUR
TI  - Recursive Bayesian computation facilitates adaptive optimal design in ecological studies
AU  - Clinton B. Leach
AU  - Perry J. Williams
AU  - Joseph M. Eisaguirre
AU  - Jamie N. Womble
AU  - Michael R. Bower
AU  - Mevin B. Hooten
PY  - 2021
JO  - Ecology
DO  - 10.1002/ecy.3573
UR  - https://doi.org/10.1002/ecy.3573
ER  -

APA

Leach, C. B., Williams, P. J., Eisaguirre, J. M., Womble, J. N., Bower, M. R., & Hooten, M. B. (2021). Recursive Bayesian computation facilitates adaptive optimal design in ecological studies. Ecology. https://doi.org/10.1002/ecy.3573

Source records

crossref · retrieved 2026-09-25T12:19:45.266Z