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Simulator of the Lotka-Volterra prey-predator system with demographic and observational noise and biases

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florent-leclercq/lotkavolterra_simulator

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Lotka-Volterra simulator

arXiv GitHub version GitHub commits GPLv3 license PyPI version Website florent-leclercq.eu

Simulator of the Lotka-Volterra prey-predator system, with demographic and observational noise and biases.

Installation

This is a standard, low-weight python package, written with python 3. It is packaged at https://pypi.org and can be installed using pip:

pip install lotkavolterra-simulator

Alternatively it is possible to clone the Github repository and to install using:

pip install .

Documentation

The model is described in section III of Leclercq (2022). The jupyter notebook simulations.ipynb illustrates how to run the code and plot prey and predator theoretical and observed number functions.

This code has been designed to illustrate concepts in simulation-based inference. It is used in pySELFI from version 2.0.

Limited user-support may be asked from the main author, Florent Leclercq.

Contributors

Reference

To acknowledge the use of lotkavolterra_simulator in research papers, please cite the paper Leclercq (2022):

Simulation-based inference of Bayesian hierarchical models while checking for model misspecification
F. Leclercq
Proceedings of the 41st International Conference on Bayesian and Maximum Entropy methods in Science and Engineering (MaxEnt2022), 18-22 July 2022, Paris, France
Physical Sciences Forum 5, 4 (2022), arXiv:2209.11057 [astro-ph.CO] [ADS] [pdf]

@ARTICLE{lotkavolterra_simulator,
    author = {{Leclercq}, Florent},
    title = "{Simulation-based inference of Bayesian hierarchical models while checking for model misspecification}",
    journal = {Physical Sciences Forum},
    volume = 5,
    pages = 4,
    doi = {10.3390/psf2022005004},
    keywords = {Statistics - Methodology, Astrophysics - Instrumentation and Methods for Astrophysics, Mathematics - Statistics Theory, Quantitative Biology - Populations and Evolution, Statistics - Machine Learning},
    year = 2022,
    month = sep,
    eid = {arXiv:2209.11057},
    pages = {arXiv:2209.11057},
    archivePrefix = {arXiv},
    eprint = {2209.11057},
    primaryClass = {stat.ME},
    }

License

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. By downloading and using lotkavolterra_simulator, you agree to the LICENSE, distributed with the source code in a text file of the same name.