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 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 . 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 Config/pak/sysreqs: libicu-dev libssl-dev Repository: https://robjhyndman.r-universe.dev Date/Publication: 2022-10-01 06:51:19 UTC RemoteUrl: https://github.com/thiyangt/seer RemoteRef: HEAD RemoteSha: abd4c2aa172809146df850db2da64310fa4ae98e NeedsCompilation: no Packaged: 2026-06-14 00:20:51 UTC; root Author: Thiyanga Talagala [aut, cre] (ORCID: ), Rob J Hyndman [ths, aut] (ORCID: ), George Athanasopoulos [ths, aut]