greybox: Toolbox for Model Building and Forecasting (original) (raw)

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: 2.0.6
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, forecast
Published: 2025-09-03
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
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,
In views: Distributions, TimeSeries
CRAN checks: greybox results

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