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r-greybox

Community

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.

Installation

To install this package, run one of the following:

Conda
$conda install teamcore::r-greybox

Usage Tracking

0.2.2
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Downloads (Last 6 months): 0

About

Summary

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.

Last Updated

Aug 1, 2018 at 16:31

License

GPL (>= 2)

Supported Platforms

linux-ppc64le
linux-64
linux-aarch64
linux-armv7l
macOS-64
linux-armv6l
linux-32