atsa-es/fish550-2025
Apr 2025 – May 2025
2 Months active
Languages Used
HTMLJavaScriptMarkdownRR Markdown
Technical Skills
ARIMAARIMA ModelingARIMA ModelsData AnalysisData VisualizationData Wrangling
LilacHo
PROFILE
Lilacho
Hong Zhang developed a suite of analytical workflows and reporting templates for the atsa-es/fish550-2025 repository, focusing on time series forecasting and statistical modeling for fisheries data. Leveraging R and R Markdown, Hong implemented ARIMA, ETS, and MARSS models to enable reproducible analyses and streamlined report generation. The work included dynamic factor analysis, hidden Markov models, and dynamic linear models, with an emphasis on data wrangling, documentation, and technical writing. By standardizing report delivery and improving test artifact management, Hong enhanced onboarding efficiency and facilitated clearer model interpretation, supporting data-driven decision making and more accurate forecasting for project stakeholders.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
36Total
Bugs
0
Commits
36
Features
6
Lines of code
38,088
Activity Months2
Your Network
8 people
Work History
May 2025
17 Commits • 3 Features
May 1, 2025Month: 2025-05. Focused on delivering end-to-end analytical features and improving documentation across Lab 3 DFA, Lab 4 HMM, and Lab 5 DLM projects in the atsa-es/fish550-2025 repository. The work produced robust modeling reports, improved report readability, and prepared the project for reproducible analyses and stakeholder communication. Notable improvements include updated DFA documentation with interpretation guidance, HMM-based analysis and cleanup for PDO data with stability checks, and comprehensive Lab 5 reports with forecasting and covariate analyses; a minor bug fix in Lab 3 and formatting/structure cleanups in Lab 4. The changes enhance business value by enabling more accurate forecasting and clearer model interpretations for decision-makers.
17 Commits • 3 Features
May 1, 2025Month: 2025-05. Focused on delivering end-to-end analytical features and improving documentation across Lab 3 DFA, Lab 4 HMM, and Lab 5 DLM projects in the atsa-es/fish550-2025 repository. The work produced robust modeling reports, improved report readability, and prepared the project for reproducible analyses and stakeholder communication. Notable improvements include updated DFA documentation with interpretation guidance, HMM-based analysis and cleanup for PDO data with stability checks, and comprehensive Lab 5 reports with forecasting and covariate analyses; a minor bug fix in Lab 3 and formatting/structure cleanups in Lab 4. The changes enhance business value by enabling more accurate forecasting and clearer model interpretations for decision-makers.
May 2025
April 2025
19 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for atsa-es/fish550-2025: Delivered core lab scaffolding, forecasting templates, and MARSS analysis setup across Lab 1 and Lab 2. Achieved reproducible workflows, improved test artifact lifecycle, and enhanced reporting quality, enabling faster onboarding and data-driven decision making.
April 2025
19 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for atsa-es/fish550-2025: Delivered core lab scaffolding, forecasting templates, and MARSS analysis setup across Lab 1 and Lab 2. Achieved reproducible workflows, improved test artifact lifecycle, and enhanced reporting quality, enabling faster onboarding and data-driven decision making.
Activity
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Quality Metrics
Correctness86.6%
Maintainability84.0%
Architecture81.0%
Performance79.4%
AI Usage26.6%
Skills & Technologies
Programming Languages
HTMLJavaScriptMarkdownRR Markdown
Technical Skills
ARIMAARIMA ModelingARIMA ModelsData AnalysisData VisualizationData WranglingDocumentationDynamic Factor AnalysisETS ModelsFile ManagementForecastingHidden Markov ModelsMARSS PackageRR Markdown
Repositories Contributed To
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