DESCRIPTION

Package: seer
Type: Package
Title: Feature-Based Forecast Model Selection 
Version: 1.1.8
Authors@R: c(
    person("Thiyanga", "Talagala", email = "tstalagala@gmail.com", role = c("aut", "cre"), comment=c(ORCID = "0000-0002-0656-9789")),
    person("Rob J", "Hyndman", role = c("ths", "aut"), comment = c(ORCID = "0000-0002-2140-5352")),
    person("George", "Athanasopoulos", role = c("ths", "aut")))
Maintainer: Thiyanga Talagala <tstalagala@gmail.com>
Description: A novel meta-learning framework for forecast model selection using time series features. Many applications require a large number of time series to be forecast. Providing better forecasts for these time series is important in decision and policy making. We propose a classification framework which selects forecast models based on features calculated from the time series. We call this framework FFORMS (Feature-based FORecast Model Selection). FFORMS builds a mapping that relates the features of time series to the best forecast model using a random forest. 'seer' package is the implementation of the FFORMS algorithm. For more details see our paper at <https://www.monash.edu/business/econometrics-and-business-statistics/research/publications/ebs/wp06-2018.pdf>.
License: GPL-3
URL: https://thiyangt.github.io/seer/
BugReports: https://github.com/thiyangt/seer/issues
Depends:
    R (>= 3.2.3)
Imports:
        stats,
        urca,
        forecast (>= 8.3),
        dplyr,
        magrittr,
        randomForest,
        forecTheta,
        stringr,
        tibble,
        purrr,
        future,
        furrr,
        utils,
        tsfeatures
Encoding: UTF-8
RoxygenNote: 7.2.1
Suggests: 
    testthat (>= 2.1.0),
    covr,
    repmis,
    knitr,
    rmarkdown,
    ggplot2,
    tidyr,
    Mcomp,
    GGally