Imports: forecast, stats, graphics, utils, lamW
Suggests: smooth, doMC, doParallel, foreach, numDeriv, testthat,

Title: Toolbox for Model Building and Forecasting
Description: 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
regressions 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.

regression model problem and more. Models developed in the package are tailored
Imports: forecast, stats, graphics, utils, lamW, numDeriv, nloptr
Suggests: smooth, doMC, doParallel, foreach, truncreg, testthat,

Package: greybox
Type: Package
Title: Toolbox for Model Building and Forecasting
Version: 0.3.1
Date: 2018-09-07
Authors@R: person("Ivan", "Svetunkov", email = "ivan@svetunkov.ru", role = c("aut", "cre"),
comment="Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK")
URL: https://github.com/config-i1/greybox
BugReports: https://github.com/config-i1/greybox/issues
Description: 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.
License: GPL (>= 2)
Depends: R (>= 3.0.2)
Imports: forecast, stats, graphics, utils, lamW, numDeriv, nloptr
Suggests: smooth, doMC, doParallel, foreach, testthat, rmarkdown, knitr
RoxygenNote: 6.1.0
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-09-10 22:11:58 UTC; isvetunkov
Author: Ivan Svetunkov [aut, cre] (Lecturer at Centre for Marketing Analytics
and Forecasting, Lancaster University, UK)
Maintainer: Ivan Svetunkov <ivan@svetunkov.ru>
Repository: CRAN
Date/Publication: 2018-09-10 23:00:03 UTC