Robust Trend-Cycle Decomposition for Macroeconomic Time Series R package MacroFilters version 0.1.0 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>. Software Depends: R (>= 3.5.0) Imports: Matrix, mboost, tseries Suggests: data.table, ggplot2, knitr, rmarkdown, scales, strucchange, testthat (>= 3.0.0), usethis, xts, zoo Michal Kinel <michal.kinel@gmail.com> Comprehensive R Archive Network (CRAN) Michal Kinel [aut, cre] (ORCID: <https://orcid.org/0009-0007-3295-7199>) MIT + file LICENSE (https://CRAN.R-project.org/package=MacroFilters/LICENSE) 2026-05-27 application/tgz https://CRAN.R-project.org/package=MacroFilters doi:10.32614/CRAN.package.MacroFilters en-US