Reproducible Discrete-Event Simulation in Python and R
Experimentation
β Sensitivity analysis
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Python
R
Reproducible Discrete-Event Simulation in Python and R
Project
STARS
Introduction
Reproducibility and RAPs
Guidelines
Open-source languages
Example conceptual models π©Ίπ§
Setup
Version control
Environments
Structuring as a package
Code organisation
Model inputs
Input modelling
Input data management
Parameters from script
Parameters from file
Parameter validation
Model building
Randomness
Entity generation
Entity processing
Output analysis
Initialisation bias
Performance measures
β Replications
β Number of replications
β Parallel processing
Experimentation
β Scenario analysis
β Sensitivity analysis
Verification & validation
β Logging
β Tests
β Validation
Style & documentation
Linting
Docstrings
β Documentation
β GitHub actions
Reports & manuscripts
β Producing tables and figures
β Full run
Collaboration & sharing
β Peer review
β Licensing
β Sharing and archiving
Citation
β Changelog
Further information
β Acknowledgements
Experimentation
β Sensitivity analysis
β Sensitivity analysis
π
Reproducibility guidelines:
STARS Reproducibility Recommendations (β): Provide code for all scenarios and sensitivity analyses.
β Scenario analysis
β Logging