The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

seer: Feature-Based Forecast Model Selection

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>.

Version: 1.1.8
Depends: R (≥ 3.2.3)
Imports: stats, urca, forecast (≥ 8.3), dplyr, magrittr, randomForest, forecTheta, stringr, tibble, purrr, future, furrr, utils, tsfeatures
Suggests: testthat (≥ 2.1.0), covr, repmis, knitr, rmarkdown, ggplot2, tidyr, Mcomp, GGally
Published: 2022-10-01
DOI: 10.32614/CRAN.package.seer
Author: Thiyanga Talagala ORCID iD [aut, cre], Rob J Hyndman ORCID iD [ths, aut], George Athanasopoulos [ths, aut]
Maintainer: Thiyanga Talagala <tstalagala at gmail.com>
BugReports: https://github.com/thiyangt/seer/issues
License: GPL-3
URL: https://thiyangt.github.io/seer/
NeedsCompilation: no
Materials: README
In views: TimeSeries
CRAN checks: seer results

Documentation:

Reference manual: seer.pdf

Downloads:

Package source: seer_1.1.8.tar.gz
Windows binaries: r-devel: seer_1.1.8.zip, r-release: seer_1.1.8.zip, r-oldrel: seer_1.1.8.zip
macOS binaries: r-release (arm64): seer_1.1.8.tgz, r-oldrel (arm64): seer_1.1.8.tgz, r-release (x86_64): seer_1.1.8.tgz, r-oldrel (x86_64): seer_1.1.8.tgz
Old sources: seer archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=seer to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.