MacroFilters
0.2.1Robust Trend-Cycle Decomposition for Macroeconomic Time Series
Overview
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.
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- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-05-287 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 88%
- Documented parameters
- 100%
- Return-value docs
- 80%
- References docs
- 33%
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Code & Tests
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2 releases. Pick two to compare their code metrics. R releases are shown for context.
- 0.2.1Latest
- 0.1.02026-05-28
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-05-28
- Total releases
- 2 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5
- Bundled data
- 11 KB / 3 files
- Download size
- 1.1 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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