{ "_id": "6a10339cacfb0bcc41c9866b", "Package": "GACE", "Title": "Generalized Adaptive Capped Estimator for Time Series\nForecasting", "Version": "1.0.0", "Authors@R": "person(given = \"Vinodhkumar\",\nfamily = \"Gunasekaran\",\nrole = c(\"aut\", \"cre\"),\nemail = \"vinoalles@gmail.com\")", "Maintainer": "Vinodhkumar Gunasekaran ", "Description": "Provides deterministic forecasting for weekly, monthly,\nquarterly, and yearly time series using the Generalized\nAdaptive Capped Estimator. The method includes preprocessing\nsteps for handling missing and extreme values, extraction of\nmultiple growth components (including long-term, short-term,\nrolling, and drift-based signals), volatility-aware asymmetric\ncapping, optional seasonal adjustment through damped and\nnormalized seasonal factors, and a recursive forecast\nformulation with moderated growth. The main interface\n'gace_forecast()' returns forecasts in a consistent structure,\nand 'plot_gace()' offers visualization support. Related\nforecasting background is discussed in Hyndman and\nAthanasopoulos (2021) and Hyndman\nand Khandakar (2008) .The method\nextends classical extrapolative forecasting approaches and is\nsuited for operational and business planning contexts where\nstability and interpretability are important.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "URL": "https://github.com/vinoalles/GACE", "BugReports": "https://github.com/vinoalles/GACE/issues", "Repository": "https://vinoalles.r-universe.dev", "Date/Publication": "2025-11-27 16:07:39 UTC", "RemoteUrl": "https://github.com/vinoalles/gace", "RemoteRef": "HEAD", "RemoteSha": "5507d850e7e5d02daec772f2297365cb094e5f93", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-12 08:09:06 UTC", "User": "root" }, "Author": "Vinodhkumar Gunasekaran [aut, cre]", "MD5sum": "30b01a5f3d8ae9987e3e6a497f5b00dd", "_user": 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