MacroFilters
Robust Trend-Cycle Decomposition for Macroeconomic Time Series
Provides high-performance tools for macroeconomic trend extraction and filtering, specifically designed to solve the end-point problem in real-time. Implements the MacroBoost Hybrid (MBH) filter using penalized P-splines and gradient boosting. Unlike the standard Hodrick-Prescott filter, 'MacroFilters' utilizes component-wise L2-boosting with robust loss functions (Huber) to handle extreme transient shocks (e.g., COVID-19) without inducing spurious trend shifts. The algorithm includes an automated two-layer diagnostic stage for unit roots and structural breaks, optimized via corrected AICc for computational efficiency. Methodology detailed in Kinel (2026) <doi:10.2139/ssrn.6371138>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | MacroFilters_0.1.0.tar.gz |
992.4 KiB |
0.1.0 |
rolling linux/noble R-4.5 | MacroFilters_0.1.0.tar.gz |
992.3 KiB |
0.1.0 |
rolling source/ R- | MacroFilters_0.1.0.tar.gz |
977.9 KiB |
0.1.0 |
latest linux/jammy R-4.5 | MacroFilters_0.1.0.tar.gz |
992.4 KiB |
0.1.0 |
latest linux/noble R-4.5 | MacroFilters_0.1.0.tar.gz |
992.3 KiB |
0.1.0 |
latest source/ R- | MacroFilters_0.1.0.tar.gz |
977.9 KiB |
0.1.0 |
2026-04-23 source/ R- | MacroFilters_0.1.0.tar.gz |
0 B |