Using Approximate Bayesian Computation to infer sex ratios from acoustic data

Lisa Lehnen, Wigbert Schorcht, Inken Karst, Martin Biedermann, Gerald Kerth, Sebastien J. Puechmaille

Open source

DOI: 10.1371/journal.pone.0199428
Published: 2018-06-21
Container: PLOS ONE
Publisher: Public Library of Science (PLoS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0199428,
  title = {Using Approximate Bayesian Computation to infer sex ratios from acoustic data},
  author = {Lisa Lehnen and Wigbert Schorcht and Inken Karst and Martin Biedermann and Gerald Kerth and Sebastien J. Puechmaille},
  year = {2018},
  journal = {PLOS ONE},
  doi = {10.1371/journal.pone.0199428},
  url = {https://doi.org/10.1371/journal.pone.0199428}
}

RIS

TY  - JOUR
TI  - Using Approximate Bayesian Computation to infer sex ratios from acoustic data
AU  - Lisa Lehnen
AU  - Wigbert Schorcht
AU  - Inken Karst
AU  - Martin Biedermann
AU  - Gerald Kerth
AU  - Sebastien J. Puechmaille
PY  - 2018
JO  - PLOS ONE
DO  - 10.1371/journal.pone.0199428
UR  - https://doi.org/10.1371/journal.pone.0199428
ER  -

APA

Lehnen, L., Schorcht, W., Karst, I., Biedermann, M., Kerth, G., & Puechmaille, S. J. (2018). Using Approximate Bayesian Computation to infer sex ratios from acoustic data. PLOS ONE. https://doi.org/10.1371/journal.pone.0199428

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crossref · retrieved 2026-11-08T13:49:08.660Z