Implements functions and instruments for regression model building and its application to forecasting. The main scope of the package is in variables selection and models specification for cases of time series data. This includes promotional modelling, selection between different dynamic regressions with non-standard distributions of errors, selection based on cross validation, solutions to the fat regression model problem and more. Models developed in the package are tailored specifically for forecasting purposes. So as a results there are several methods that allow producing forecasts from these models and visualising them.
Version: 2.0.5 Depends: R (≥ 3.5.0) Imports: stats, generics (≥ 0.1.2), graphics, utils, pracma, nloptr, statmod, zoo, texreg, xtable, methods LinkingTo: Rcpp Suggests: smooth (≥ 3.1.0), doMC, doParallel, foreach, testthat, rmarkdown, knitr Enhances: vars Published: 2025-06-30 DOI: 10.32614/CRAN.package.greybox Author: Ivan Svetunkov [aut, cre] (Senior Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK), Yves R. Sagaert [ctb] (Visiting Research at Centre for Marketing Analytics and Forecasting, Lancaster University, UK) Maintainer: Ivan Svetunkov <ivan at svetunkov.com> BugReports: https://github.com/config-i1/greybox/issues License: LGPL-2.1 URL: https://github.com/config-i1/greybox NeedsCompilation: yes Language: en-GB Materials: README NEWS In views: Distributions, TimeSeries CRAN checks: greybox resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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