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MacroFilters  

Robust Trend-Cycle Decomposition for Macroeconomic Time Series
View on CRAN: Click here


Download and install MacroFilters package within the R console
Install from CRAN:
install.packages("MacroFilters")

Install from Github:
library("remotes")
install_github("cran/MacroFilters")

Install by package version:
library("remotes")
install_version("MacroFilters", "0.2.1")



Attach the package and use:
library("MacroFilters")
Maintained by
Michal Kinel
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-05-27
Latest Update: 2026-05-27
Description:
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>.
How to cite:
Michal Kinel (2026). MacroFilters: Robust Trend-Cycle Decomposition for Macroeconomic Time Series. R package version 0.2.1, https://cran.r-project.org/web/packages/MacroFilters. Accessed 07 Oct. 2026.
Previous versions and publish date:
0.1.0 (2026-05-27 22:00), (2026-07-09 08:10)
Other packages that cited MacroFilters R package
View MacroFilters citation profile
Other R packages that MacroFilters depends, imports, suggests or enhances
Complete documentation for MacroFilters
Functions, R codes and Examples using the MacroFilters R package
Full MacroFilters package functions and examples
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