Generalized Adaptive Capped Estimator for Time Series Forecasting R package GACE version 1.0.0 Provides deterministic forecasting for weekly, monthly, quarterly, and yearly time series using the Generalized Adaptive Capped Estimator. The method includes preprocessing for missing and extreme values, extraction of multiple growth components (including long-term, short-term, rolling, and drift-based signals), volatility-aware asymmetric capping, optional seasonal adjustment via damped and normalized seasonal factors, and a recursive forecast formulation with moderated growth. The package includes a user-facing forecasting interface and a plotting helper for visualization. Related forecasting background is discussed in Hyndman and Athanasopoulos (2021) <https://otexts.com/fpp3/> and Hyndman and Khandakar (2008) <doi:10.18637/jss.v027.i03>. The method extends classical extrapolative forecasting approaches and is suited for operational and business planning contexts where stability and interpretability are important. Software Depends: R (>= 4.1.0) Imports: ggplot2, stats, utils Suggests: testthat (>= 3.0.0), knitr, rmarkdown, covr, forecast Vinodhkumar Gunasekaran <vinoalles@gmail.com> Comprehensive R Archive Network (CRAN) Vinodhkumar Gunasekaran [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=GACE/LICENSE) 2025-12-11 application/tgz https://CRAN.R-project.org/package=GACE doi:10.32614/CRAN.package.GACE