Deutsch Intern
    Chair of Computer Science II - Software Engineering



    Telescope is a hybrid forecasting tool written in R and designed to perform multi-step-ahead forecasts for univariate time series while maintaining a short runtime. The forecasting method is based on STL time series decomposition. To achieve better forecasting results, Telescope uses clustering techniques for categorical information creation and ARIMA, ANN, and XGBoost as forecasting methods. Telescope users can pass a matrix of timestamps and observation values, set the length of the forecasting horizon, and also set various optional parameters.


    • Telescope is published under GPL v3 here
    • ITISE 2017 Presentation Slides available here
    • FAS Tutorial on "Best practices for Time Series Forecasting" Slides available here


    This package can be installed in R by using the following commands:


    For unknown reasons, install_gitub does not work under all Windows versions. Therefore the package can alternatively be installed in R with the following commands:

    remotes::install_url(url="https://github.com/DescartesResearch/telescope/archive/master.zip", INSTALL_opt= "--no-multiarch")


    Publication system is temporarily out of service!

    Mailing List

    To stay updated on our tools, please subscribe to our descartes-tools mailing list (low traffic, only announcements related to our tools)
    Your E-mail address:
    Your Name (optional):