mcgoodman/widow-assessment-update
Apr 2025 – May 2025
2 Months active
Languages Used
RShellC
Technical Skills
Data AnalysisR ProgrammingStatistical ModelingData VisualizationFisheries ScienceParameter Estimation
agdedrick
PROFILE
Agdedrick
Developed and refined an end-to-end Jitter Analysis Pipeline for the widow-assessment-update repository, enabling scalable uncertainty quantification and robust model assessment in fisheries science. Leveraging R and Shell scripting, the workflow automated directory setup, replicated base models, and executed multiple jittered runs using r4ss, with outputs compared through statistical modeling and data visualization. Enhancements included best-parameter preservation, streamlined jitter runs, and improved reporting clarity, reducing analysis workload and supporting reproducible research. Diagnostic plots and parameter extraction features strengthened model robustness, while updates to control and data files ensured maintainable workflows and more reliable forecasting for ongoing fisheries stock assessments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
7Total
Bugs
0
Commits
7
Features
3
Lines of code
6,454
Activity Months2
Your Network
13 peopleShared Repositories
13
alaiamMember
Alberto RovelliniMember
Maurice Codespoti GoodmanMember
iantaylor-NOAAMember
Kiva OkenMember
Laura.SpencerMember
Laura H SpencerMember
Megan FeddernMember
MichaelMember
Work History
May 2025
4 Commits • 2 Features
May 1, 2025May 2025: Delivered two feature enhancements in the widow-assessment-update repo to improve jitter analysis, reduce analysis workload, and strengthen reporting. Key outcomes include reusable best-parameter preservation, streamlined jitter runs, clearer visualization, and more stable model parameters. These changes accelerate decision support and improve forecasting reliability while maintaining maintainable code and data workflows.
4 Commits • 2 Features
May 1, 2025May 2025: Delivered two feature enhancements in the widow-assessment-update repo to improve jitter analysis, reduce analysis workload, and strengthen reporting. Key outcomes include reusable best-parameter preservation, streamlined jitter runs, clearer visualization, and more stable model parameters. These changes accelerate decision support and improve forecasting reliability while maintaining maintainable code and data workflows.
May 2025
April 2025
3 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for mcgoodman/widow-assessment-update. Key accomplishment: delivered an end-to-end Jitter Analysis Pipeline for the 2025 Base Model, enabling scalable uncertainty quantification and evidence-based model assessment. The pipeline includes directory setup, copying the base model, running multiple jittered replicates with r4ss, and comparing log-likelihoods with visualizations. Expanded jittering capacity with more runs (njitters) and added minimum-likelihood analysis with plots and parameter extraction. Demonstrated automation and reproducibility across the jitter workflow, setting the stage for ongoing model evaluation and reporting.
April 2025
3 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for mcgoodman/widow-assessment-update. Key accomplishment: delivered an end-to-end Jitter Analysis Pipeline for the 2025 Base Model, enabling scalable uncertainty quantification and evidence-based model assessment. The pipeline includes directory setup, copying the base model, running multiple jittered replicates with r4ss, and comparing log-likelihoods with visualizations. Expanded jittering capacity with more runs (njitters) and added minimum-likelihood analysis with plots and parameter extraction. Demonstrated automation and reproducibility across the jitter workflow, setting the stage for ongoing model evaluation and reporting.
Activity
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Quality Metrics
Correctness82.8%
Maintainability82.8%
Architecture80.0%
Performance65.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
CRShell
Technical Skills
Data AnalysisData VisualizationFisheries ScienceParameter EstimationR ProgrammingStatistical Modeling
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