Package: MacroFilters
Title: Robust Trend-Cycle Decomposition for Macroeconomic Time Series
Version: 0.1.0
Authors@R: 
    person("Michal", "Kinel", , "michal.kinel@gmail.com", role = c("aut", "cre"),
           comment = c(ORCID = "0009-0007-3295-7199"))
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>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.3.3
URL: https://github.com/michal0091/MacroFilters,
        https://michal0091.github.io/MacroFilters/
BugReports: https://github.com/michal0091/MacroFilters/issues
Imports: Matrix, mboost, tseries
Suggests: data.table, ggplot2, knitr, rmarkdown, scales, strucchange,
        testthat (>= 3.0.0), usethis, xts, zoo
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-20 16:46:23 UTC; miki
Author: Michal Kinel [aut, cre] (ORCID:
    <https://orcid.org/0009-0007-3295-7199>)
Maintainer: Michal Kinel <michal.kinel@gmail.com>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2026-05-27 20:00:07 UTC
