atsa-es/fish550-2025
Apr 2025 – May 2025
2 Months active
Languages Used
HTMLJavaScriptMarkdownRCSS
Technical Skills
ARIMA ModelsData AnalysisData VisualizationData WranglingFront End DevelopmentMARSS
Matheus de Barros
PROFILE
Matheus De Barros
Matheus Barros Teixeira developed advanced time series forecasting and ecological modeling features for the atsa-es/fish550-2025 repository, focusing on ARIMA and MARSS models to analyze salmon productivity and zooplankton dynamics. He implemented dynamic state-space models and integrated covariate analysis, using R and JavaScript to deliver reproducible reports and interactive web interfaces. His work included robust data wrangling, visualization, and UI/UX enhancements with Bootstrap and CSS, improving both analytical depth and user experience. By addressing workflow stability and model evaluation accuracy, Matheus ensured reliable results and streamlined reporting, demonstrating strong technical proficiency in statistical modeling and front-end development.
Overall Statistics
Feature vs Bugs
71%Features
Repository Contributions
25Total
Bugs
2
Commits
25
Features
5
Lines of code
595,156
Activity Months2
Your Network
8 people
Work History
May 2025
10 Commits • 3 Features
May 1, 2025May 2025 monthly summary for atsa-es/fish550-2025: Delivered key modeling and UI enhancements that strengthen ecological inference, forecasting, and user experience. Implemented dynamic state-space modeling (DFA/HMM) for zooplankton and grazer dynamics with covariates and AICc-based model comparisons, advanced DLMs for salmon productivity with covariates using MARSS, and comprehensive web UI improvements for the lab project. Fixed workflow instability by disabling the H_inv_2 calculation in the analysis script, stabilizing results and pipelines. Visualizations and documentation accompany the delivered work, enabling faster interpretation and reuse.
10 Commits • 3 Features
May 1, 2025May 2025 monthly summary for atsa-es/fish550-2025: Delivered key modeling and UI enhancements that strengthen ecological inference, forecasting, and user experience. Implemented dynamic state-space modeling (DFA/HMM) for zooplankton and grazer dynamics with covariates and AICc-based model comparisons, advanced DLMs for salmon productivity with covariates using MARSS, and comprehensive web UI improvements for the lab project. Fixed workflow instability by disabling the H_inv_2 calculation in the analysis script, stabilizing results and pipelines. Visualizations and documentation accompany the delivered work, enabling faster interpretation and reuse.
May 2025
April 2025
15 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for atsa-es/fish550-2025 focusing on delivering ARIMA-based forecasting lab capabilities, MARSS-informed final reports, and a critical bug fix to improve model evaluation reliability. The work emphasizes business value through robust forecasting, reproducible reporting, and polished UI for stakeholder communication.
April 2025
15 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for atsa-es/fish550-2025 focusing on delivering ARIMA-based forecasting lab capabilities, MARSS-informed final reports, and a critical bug fix to improve model evaluation reliability. The work emphasizes business value through robust forecasting, reproducible reporting, and polished UI for stakeholder communication.
Activity
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Quality Metrics
Correctness72.8%
Maintainability72.8%
Architecture71.2%
Performance63.2%
AI Usage28.0%
Skills & Technologies
Programming Languages
CSSHTMLJavaScriptMarkdownR
Technical Skills
ARIMA ModelsBootstrapCSSData AnalysisData VisualizationData WranglingFront End DevelopmentHidden Markov ModelsJavaScriptMARSSMARSS ModelsRR ProgrammingReport GenerationStatistical Modeling
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