45 refactoring to log ratio regression#46
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December 11, 2025 22:40
Infrastructure improvements for handling full-year data within 8GB container: Added: - scripts/process_csvs_batched_optimized.py: Batched CSV processing (5k files/batch) * Prevents OOM on 30k+ file datasets * Streams through data without full materialization * Tested on July 2023 (30,027 files) - tests/diagnose_bg_density_v2.py: Block-group sampling density diagnostic * Checks household density per block group * Validates cluster share variance * Provides recommendations for sample size Modified: - analysis/clustering/prepare_clustering_data_households.py: Multi-file input support * Accepts multiple parquet files via --input file1 file2 ... * Loads and merges manifests from all input files * Enables analysis on split datasets (e.g., jan_nov.parquet + dec.parquet) - .gitignore: Exclude generated Quarto HTML files This checkpoint precedes the Stage 2 regression refactor (multinomial logit → log-ratio regression).
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Duplicate of #44, closing |
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Methodology Update: Log-Ratio Regression on Block Group Composition
Summary
This PR refactors Stage 2 regression to use log-ratio regression instead of multinomial logistic regression, addressing feedback on the appropriate unit of analysis for demographic modeling.
What Changed
Previous Approach = Multinomial Logit
New Approach (Log-Ratio Regression)
Infrastructure Improvements (handling high-volume processing of the raw AWS CSVs)
Also includes memory-efficient processing improvements for large datasets: