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A Rapid Method for Modeling a Variable Cycle Engine
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Explaining empirical dynamic modelling using verbal, graphical and mathematical approaches
Andrew M Edwards1,2, Luke A Rogers1, Carrie A Holt1
1Pacific Biological Station Fisheries and Oceans Canada Nanaimo British Columbia Canada.
Ecology and Evolution
|May 16, 2024
Summary
Empirical dynamic modelling (EDM) offers a new way to understand ecosystem dynamics by visualizing time-series data in multi-dimensional space. This study clarifies EDM
Area of Science:
- Ecology
- Complex Systems Science
- Time Series Analysis
Background:
- Empirical dynamic modelling (EDM) is increasingly used in ecological studies.
- Existing literature lacks comprehensive explanations, hindering understanding and reproducibility.
- EDM analyzes ecological system dynamics using time-series data.
Purpose of the Study:
- Provide a detailed introduction to Empirical Dynamic Modelling (EDM).
- Clarify the mathematical underpinnings and practical application of EDM algorithms.
- Introduce the pbsEDM R package to enhance understanding and application of EDM in ecology.
Main Methods:
- Graphical and mathematical explanations of EDM principles.
- Detailed walkthrough of the simplex and S-map algorithms.
- Development and application of the pbsEDM R package for ecological data.
Main Results:
- A clear, step-by-step explanation of EDM, including mathematical formulations.
- Identification of points to exclude in multi-dimensional space for accurate predictions.
- A novel method for excluding library points, beneficial for short ecological time series.
Conclusions:
- Improved clarity of EDM methods is crucial for its wider adoption in ecology.
- The pbsEDM package facilitates reproducibility and application of EDM.
- Enhanced understanding of EDM will support natural resource management through better ecological forecasting.
Keywords:
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